User:Rainbowdolph/sandbox

=== Article Evaluation (Information privacy) === Content


 * The section on cable television might be a little out of date in today's society.
 * The legality subsection isn't really evaluated on, it was a little hard to follow.
 * The Safe Harbor program and passenger name record issues subsection seems a little out of date. If there was information on how it's presently doing, that would be helpful.

Tone


 * Mostly neutral, could not find any subjective words or ideas.
 * There is no perspective of the opposition. There was an idea about how people can be prone to cyberstalking or information collection from an opposing side. While this is mostly seen to have a negative connotation, what about elaborating on companies that take this information to strengthen their marketing strategies (just an example).

Sources


 * Sources are linked and somewhat neutral at first impression. I clicked on a USA Today news article which is prone to being subjective, but there were just quotes on people's perspectives, which did not show author bias.
 * One of the sources leads to what I believe is a database that holds several materials, not a single artifact. However, I believe the link of ".gov" to be trustworthy and whichever of the three sources for the article is reliable.

Talk


 * There seems to have been several instances of subjective opinions in the article that, as of today, have been revised.
 * There was also some combination about this topic overlapping with already existing ideas, such as digital privacy.

Article Evaluation (Phone hacking)
Content


 * I don't see how relevant determining where the terms first got coined was besides the fact that it would shed some light on events that would not otherwise be heard of.
 * Besides the small section of legality, I think it could be expanded more as to the different legal things as well as services like the NSA that has something related to this topic.

Tone


 * There's one sentence pointing out about flaws in the implementation of the GSM encryption algorithm but it isn't really evaluated on, so there aren't any facts that support whether or not these flaws are accurate.

Sources


 * One article I clicked on was from CNN and there was a focus on smart phones, which I believe might be better for emphasizing this topic, especially as technology develops, phone hacking relating to smartphones are more relevant to people today. There were some subjective opinions, but there were quoted, so it wasn't the perspective of the author.
 * A different source from BBC basically reiterated an interview on a single question "how easy is it to hack a mobile". There were almost no original ideas in the article, only quotes from the interviewee. On a contrasting side, an article from The Register was using very aggressive terms, such as "harasser" and "fraudulently", and didn't have many quotes, only a lot of recalling of events that might be related to phone hacking, including phone hacking's involvement with Pablo Escobar.

Talk


 * The main point that was being talked about on this article was that it was not a clear topic. Phone hacking is very general and could be related to several terms, but this page was not defined enough to be able to find resources to support it, rather re-direct to other issues of similar titles.
 * It is a potential in several WikiProjects, mostly related to some sort of comput*. Mostly rated as "start-class" and there are not that many rankings I believe proves that this article is still under development.

Plans to contribute:
I am creating a new article because ride sharing is a relatively new technology and there are several things related to privacy with this. These ideas could include: cameras inside the car, privacy with location tracking of apps, certain rights after being in a different person's vehicle. I plan on addressing the privacy that people think of when sharing information with random people to get to destinations, which could branch further into like a driver tracking a religiously affiliated location they dropped off their rider and can later use.

simhhyena peer review
I like the way that your article is broken up into the sections, and I think it certainly has good bones. I like that you used a lot of examples, and that in your sections, the information was laid out very clearly in lists. It will be easy for the average Wikipedia audience to follow. However, at the same time, I think you should put some of your information into more paragraph like forms, which will probably happen over time in working with your article. I also liked that you included specific technical information and policies as they help to perhaps add hyperlinks to those sort of pages to see if they connect to your Wikipedia article. Overall, I definitely like your article and I look forward to what it'll look like as you continue editing! I also think that you should try to balance out having lists with having more so description as this will allow for more comprehensible understanding.

Bibliography - 20 Sources
Brown, E. (2017). Fare Trade: Reconciling Public Safety and Gender Discrimination in Single-Sex Ridesharing. Yale Law & Policy Review, 35(2), 367–406. Retrieved from https://libproxy.berkeley.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3da9h%26AN%3d126100185%26site%3deds-live

This research is primarily focusing on females who are utilizing ride-sharing applications and how their sense of security ties into their privacy. There is a large section on spatial privacy and how this is a little different because it is more gender specific than data privacy which has been the focus of most other papers. The private is used more to describe a setting where the rider is in, public vs. private. The argument is more focused on how public safety for females holy just as much important as their privacy. The paper then branches out to argue that not only transportation, but in clubs there are issues with customer gender privacy. However, the focus on ride sharing and women focuses on trying to create a safer environment for single women riders by hiring women drivers because it creates a safer space. The source however does focus a lot more on safety concerns, rather than possible solutions to protecting privacy. It goes into talking about drivers and riders alike need protection against those who can take advantage of their situation, but it’s protecting the women’s image and the fact that they are female not that men and women are equally in danger of losing their private information. This source seems reliable because it touches a lot of points on public safety and gender discrimination and references a lot of outside citations to back up its data. This source does not appear to be biased, however, it does take a strong stance supporting the protection of females in the ride sharing services. It does not provide a contradictory view, only However, on a broader scope this paper does not solely target ride sharing, it focuses on several different kinds of transportation that could pose threats to people but specifically females. On the contrary, this paper is a good source for providing information on solutions to how to fix gender equality in ride sharing but also taking care of privacy of female riders, not with their data, but with their physical identities. This paper is structured a little bit differently than my other sources because it interprets privacy a different way instead of referring to the digital data that users input, this is more of a physical privacy that someone’s identity can face in public in the moment.

Chen, Jengchung V., William Ross and Shaoyu F. Huang. 2008. "Privacy, Trust, and Justice Considerations for Location-Based Mobile Telecommunication Services."Info 10(4):30-45 ( https://search.proquest.com/docview/56790456?accountid=14496 ).

This source talks about the presence of location-based services using the already existing software of the global positioning satellite systems which have opened up a whole new amount of opportunities in telephones. This paper is intending to locate the benefits and issues about these new types of services. It directly addresses the privacy issues with location-based services, something that is really important to my topic because it is practically the main argument. Information privacy is different than just regular privacy because it is not just something physical but it also includes something on the digital world, which adds several more complications. The process of phones communicating with one another is then discussed. The paper then goes into a similar tone about the amount of trust that each party must have for the other because that is what makes the business go. When the user agrees to the terms of the services, they are putting trust in that the app will protect them to some extent. This information appears to be reliable, it does cite a lot of in-text citations as well as referencing several government related activities which help backup and support if people are afraid of the several threats with location based services. The targeted audience are those are curious about what are potential threats of these services as the technology has just started expanding and these services are still new and people do not know much about them, it is more aimed towards a little bit earlier than today because in the current day, the knowledge and ability that our technology has has already surpassed what this paper was addressing, which was in the very early stages of this never before seen technology. The difficulty of this piece is it is actually not that hard to follow. There is not any excessive jargon that makes it unreadable or hard to follow and it is broken down into its three main components and does not overlap on any so it makes each argument very clear. THe paper has helped me be able to create a more clear vision of what my argument for privacy is. Before I was confused as to what exactly the privacy was because I was not sure of how much privacy was included, just the person, just the data, just the location, but after reading this source it helped clear up that I should be including all, but they just refer to different aspects of the application.

Cox, W. (2016). Driverless Cars and the City: Sharing Cars, Not Rides. Cityscape, 18(3), 197-204. Retrieved from http://www.jstor.org.libproxy.berkeley.edu/stable/26328283

This article is about how when there are new advancements in technology, driverless cars are a rising subject of interest. The most intense aspect related to driverless cars are the potential to be hacked into as well as concerns with the artificial intelligence. Ridesharing is seen as an alternative that is very friendly yet having a personal security as its main issue. There is some mention about leasing cars and the reason for investing into those but then there is talk about the market sizing for cars and what would be an ideal place to target for the introduction of driverless cars. There is then a step back looking at cities in a broader scope and how they can affect development of cities because transportation is something to take into consideration when trying to best utilize the space of a city. This article is broken into subsections with very distinct and not related to the previous sections. It also does not go into very much detail and does not have any statistical information to back-up any claims in the source. This source is not as useful as I thought it would be. It mentioned in the beginning about driverless cars which could potentially turn into an autonomous form or ride-sharing or carpooling, however, the article was more about the logistics and arguing why this solution should be implemented. The source provides some pros and some cons about the implementation of this technology, both smaller scale as well as larger, like immediate effects versus thinking long term. The targeted audience is those who are thinking about if autonomous ridesharing is a viable option and things they should consider when deciding. The reading difficult of the publication is not much; it is a relatively straightforward piece and there are no graphs or tables that would provide random jargon that is hard to understand. This has not really changed my mind, but rather provided some insight that I never really thought about when thinking about this subject. The source wasn’t really specific towards the privacy aspect, although it was touched very briefly, but it was helpful in providing more context about my topic.

Damiani, M. L. (2014). Location privacy models in mobile applications: Conceptual view and research directions. GeoInformatica, 18(4), 819-842. doi: http://dx.doi.org/10.1007/s10707-014-0205-7

This source talks about how location privacy is something new with the rise in new location technologies and the location privacy metric is something that is focused on defining the framework of privacy. There are several services to mobile applications on location, location-based services, mobile sensing, geo-location services, and location sharing. There are all related topic because they all raise the issue of location and privacy. There are government related statements that shows with all these services, it does not really matter how private something is because everything in public is always being tracked. It’s just the presence of consent that gives this paper voice. There are two main enemies of private date, one being companies who want to use personal information for their own profit, and the second is putting a tracker on the user and following them to build a profile. A solution is a location privacy metric which offers some level of protection to users. The paper then goes into chronologically an application model for the proposed solution and breaks it down into what are three targets that this solution is also trying to fix and finally the application of the solution. The solution is a model that would estimate how difficult it would be for outside sources to get their hands on someone’s private information. There are several mechanisms proposed that would be helpful in hiding data including location obfuscation, perturbation, confusion and suppression, and cryptographic techniques. (citation here). Overall, this paper targeted three main points, the first was to figure out a general framework for a privacy metric that would assess the current status of how easy or difficult it is to gain access to personal information, the second was what were the main goals in privacy, which was protecting patterns and movement in real time, and the third was how to go about developing a solution from this based on models of applications how would it be implemented and created. This source seems reliable, it has footnotes and research to back up its claims. Like other resources, this paper offers a solution and does so by first defining the problems, then outlining a possible solution followed up by what are the goals and concluding with further steps of how to actually implement. This source would be helpful to those more advanced who are also thinking of a solution for these privacy issues. This lays down a framework of what a solution needs and the audience could build off of it, but putting in their own specifications. This paper is like a guideline for a solution which is not as helpful to the users but to those businesses who are trying to create a solution. This is beneficial to my topic because it helps set a foundation for how solutions can be built upon because it’s a common theme that I’ve seen in the actual solutions sources that they follow this similar set up.

Gierlack, K., Williams, S., LaTourrette, T., Anderson, J., Mayer, L., & Zmud, J. (2014). The Legal Aspect of LPR Privacy Concerns. In License Plate Readers for Law Enforcement: Opportunities and Obstacles (pp. 37-48). RAND Corporation. Retrieved from http://www.jstor.org.libproxy.berkeley.edu/stable/10.7249/j.ctt7zvzjk.12

The main point of this passage is explaining how the government is the basis behind all surveillance, even if it seems local and how license plate readers can provide a different level of surveillance. It then goes into talking about the Fourth Amendment and to what circumstances they apply to. There was one case study where a tracker was placed to track those who were suspected of drug trade. After finding out that there was illegal activity, the argument that won was there is no expectation for privacy on the open public roads. There are several cases covered which go over different ways technology has been exploited in order to track someone or bring them to political justice. This then leads into sources that are reliable because they are cases or reports that have appeared before the government so they are not just speculation, but unbiased accounts of privacy and information. This source is helpful to those who want to understand what political steps have taken in the past and what conclusion has been reached and to what degree of privacy. There are several state laws as well as court conclusions referenced in the passage from its original source. This article hasn’t really changed my way of thinking because it just brought up case studies where the law was involved with different aspects of privacy. It has just strengthened my perspective on different ways that car privacy has been invaded and then went as far as going to the government to see what governmental policies are related to trying to address the problem. This resource has not changed my perspective of my topic because it shows that privacy in transportation has been issues before and because of that there are government laws and policies that exist that address these issues. This resource helps shape my argument because it shows the extent that privacy in softwares related to cars, license recognition programs, expands and had to be taken to the government level which shows the level of involvement and seriousness of these softwares.

Hashemi, M., & Malek, M. R. (2012). Protecting location privacy in mobile geoservices using fuzzy inference systems. Computers, Environment & Urban Systems, 36(4), 311–320. https://doi-org.libproxy.berkeley.edu/10.1016/j.compenvurbsys.2011.12.002

The main point of this passage is trying to understand a different approach for different ways to protect someone’s privacy when related to mobile geoservices, which is to try and use fuzzy inference systems that would use different details to identify the user that would not be prone to organizations abusing the obtained information. Currently, location based services can reveal several sensitive pieces of information, like closest religious institutions, which can reveal the identity of the user, which organizations utilize for purely commercial purposes. The paper proposes a solution, anonymization, which protects user’s data in case of accidental breaches. There is an explanation of the fuzzy inference system and how it works and then the potential implication method in taxi drivers to see if this is an effective way of protecting people’s information because there isn’t a concrete design with anonymization that has proven to do well. There are different levels of precision that the location system can narrow down on a user. These systems turn quantitative data into qualitative data which would obscure a user’s identity and location. After a trial implementation with taxi drivers, several complications came up, mostly human misinterpretation, but in the future, investing more time into this solution and combining it with already existing solutions could provide a more effective solution. The targeted audience are those who own a device and are afraid of potential data tracking by location. They are the audience because this paper is providing a potential solution, to those who are afraid of their locations being tracked and that being used to trace back to the user, by identifying a solution that makes user data fuzzy so their tracking is not completely precise. There are data tables in here that show experimental distances of how close a tracking software was to those who had implemented the fuzzy solution. This reading has changed my way of thinking because it provides a solution that doesn’t entirely solve the problem, but is working towards it since the solution has not had enough time to mature. It sheds light on the fact that the location tracking software is still not private even when solutions have been taken to try and overcome this solution but leaves a hopeful ending because it ends optimistically that with more research and resources put into it (and specifically told what areas could be developed better) it could expand further.

He, Y., Ni, J., Wang, X., Niu, B., Li, F., & Shen, X. (2018). Privacy-Preserving Partner Selection for Ride-Sharing Services. IEEE Transactions on Vehicular Technology, 67(7), 5994–6005. https://doi.org/10.1109/TVT.2018.2809039

This source starts of of by giving background context about what the appeal to ride sharing is and then dives into a technology scheme that is centered around protecting customer privacy. There was a large section dedicated to privacy leakage and what could be lost, including an example of how Uber released over 2 billion pieces of data which shows how much these apps have of your personal information. There were some solutions suggested including pseudonyms, encryption techniques, location hiding services, etc. The paper then starts and goes into a propose a new solution, Privacy-preserving Ride-share partner Selection scheme which would address the privacy issue but not lose any efficiency of ride-sharing benefits. The paper is then split into three sections, one on encrypting locations and aiming for a broader area to drop off customers, another on focusing on time time and fuel efficiency for the riders, and the last one on optimizing time travel saving. This information is reliable in a sense that it highlights that there are ways to fix the problems with ride-sharing apps. It is not biased because it is not taking an argument, just a solution. The targeted audience are potentially those who either 1, mistrust the ride sharing apps today because they have had experiences with data invasion and are looking for a solution that addresses these needs or 2, companies that have these apps and can learn on what ways they can improve their already existing programs. The publication is not super hard to read because the solution is broken down into several sections, but there are several graphs and data that are used to describe the science behind the code, because they are proposing a new software. It does help because they are addressing possible scenarios so people have context about their app, but it is a little hard to follow the equations. This source is really helpful to my topic because it proposes a solution that ride-sharing apps are facing nowadays and splits them into three categories, one of which is mainly on privacy and user location.

JOHNSTONE, R. (2007). Not Safe Enough: Fixing Transportation Security. Issues in Science and Technology, 23(2), 51-60. Retrieved from http://www.jstor.org.libproxy.berkeley.edu/stable/43314400

The main point of the article is to address the transportation security in the United States. Since the September 11th attacks, there are several initiatives have been created by the government as well as there is just a greater awareness overall to the new system and how effective these measures can/will be. Specifically for aviation security, there has been changes that show an increase in the parameters which still contain privacy concerns, such as a no-fly list that would give airlines access to people’s information who are on the list. These parameters started applying to several different areas, ranging from the cockpit to the ground control. The rest of this article has been separated into different categories of security, from air transportation and water transportation, to land transportation. The paper then goes back and re-addresses the reason that this topic was brought into discussion, which is if this information was helpful for the reason that all these measures were implemented. There are also some unanswered questions that provides a counter-argument for all these security implementations. People were questioning the legitimacy because they were all hastily added, but the responsibility of how they would be maintained was not known and was unclear because of the rush (this included not just maintenance of activities but also financial support and other aspects). The paper then goes into a broader scope about how these issues could potentially be resolved. There are several factors that must be considered, budget, policy, international affairs, universal standards, flexibility of the system, efficiency, etc. The paper comes to conclude that there are definitely more policies that have been implemented since 9/11, however the fact that they were done so, so abruptly left a lot of room for error which if the government does not take responsibility, will have a hard time filling the spaces. This source is reliable in a sense that several government policies are drawn upon and properly cited throughout the paper to show there are policies that are currently in effect. This source does not seem biased because it doesn not take a perspective on if these methods are working or not, simply it states the policies, divided up into categories, and then bring up a holistic look at these efforts. I would recommend it to those who are seeking information about what changes have been made that protect them on certain areas of entry, land, water, or air. This information did not present me with any new knowledge, only helped provide specific examples to something that I had heard about but was not invested enough to look further into. This could help my research however because it helped establish some problems with these security measures that I can interpret and see how they could be applicable to ride-sharing and not air transportation.

Menéndez, C. K. C., Amandus, H. E., Damadi, P., Wu, N., Konda, S., & Hendricks, S. A. (2013). Effectiveness of Taxicab Security Equipment in Reducing Driver Homicide Rates. American Journal of Preventive Medicine, 45(1), 1–8. https://doi-org.libproxy.berkeley.edu/10.1016/j.amepre.2013.02.017

This article is about a study done that was testing what the installation of cameras inside taxi cabs would effect on the homicide rates of taxi drivers. The article states how out of different occupations, taxi drivers have the highest homicide rates due to the position itself. There was research done on several cities where it was comparing over the span of 15 years, the homicide rates in cities that 1) installed cameras inside taxis, 2) installed bullet-resistant partitions, or 3) had neither. The results of the researched showed that the cities that had the security cameras installed had a reduction of three times as many homicides compared to the controls but the cities that installed the partitions did not show a difference in number of homicides. The paper is structured just like an experiment, it introduces the problem, shows the layout of how the research was conducted, presents its data findings, and then analyzes the end results. The findings of this research come to the conclusion that this data is not representative of the cities which installed solely partitions being less effective than no security measures installed, only that the cities which installed security cameras did have a significant enough difference that this hypothesis is supported. However, there are several things that come up with the implementation of this technology, including testing the functionality of the cameras. However, this research does bring up a concern because while cameras are installed for driver safety, some of the camera data was missing in some cases because of the limits of cameras recording people in public. Additionally, this research could not address the usage of different safety equipments such as location tracking on the taxis which are both features that privacy must be considered. This information seems reliable because it is mostly just an analysis of research done, it was not an argumentative paper, but just was analyzing results of a study done. This source is not that helpful to my topic because it is not really related to the privacy that installing cameras into modes of transportation, but rather it is related to seeing how effective these methods that are related to privacy have on the safety of passengers. While it focuses on topics that are related to privacy, they are interpreted more on their effectiveness to stop homicide, not whether the privacy of people being recorded, not just people who commit the crime, are in any danger of being breached. This source has just provided some background information on effectiveness of security measures, so it can provide support for the pro side of having cameras inside cars.

Patil, S., Patruni, B., Potoglou, D., & Robinson, N. (2016). Public preference for data privacy – A pan-European study on metro/train surveillance. Transportation Research Part A: Policy & Practice, 92, 145–161. https://doi-org.libproxy.berkeley.edu/10.1016/j.tra.2016.08.004

Railways and metros are a vulnerable public areas that are subject to several deadly activities, ranging from robberies to terrorist attacks which have lead to changes in policy and security measures, both technological and social. However, since these do have repercussions on citizens, there must be a balance between how much the government can protect people and to what extent these invade people’s personal lives. Several questionnaires were taken and the results were used to understand the public’s responses to these new government involvements. The results of the survey showed that Europeans were in favor of using CCTV with facial detection software, while several other countries did not show a strong preference; besides Greece, who has a communist influence backing their military dictatorship, and Germany, who enforce these issues on a specific federal level rather than a general national level. This publication goes into more detail about several different European countries and their individual preferences, backed up by numerical evidence) on factors like how long and what kind of CCTV can store data or preference on physical police figures in companies or at public transportation stations. The source does not seem biased, it is more an analysis of the survey results from the public. This source would be useful for infrastructure related companies who in charge of public security. For example, there's statistical data about the "magnitude of preference in the units of utility" which explains different recognition softwares in CCTV which would be helpful knowing what type of software to install in public spaces that have shown decently strong customer preference based on their perception of their own safety. The reading difficulty is not that high because the graphs and tables are very clear on what categories were recorded on the surveys, but the actual numbers do not provide much information exactly, such as there’s a coefficient and a t-ratio under table 3a which does not really provide any indicator of good or bad numbers. This has changed my way of thinking because it provided a perspective I’ve never really thought of. First, the fact that it centers on European areas as its main audience was something that I don’t really think about. Additionally, the purpose of this paper was not as much to focus on whether or not privacy in public areas was acceptable or not, but to what extent the public would let security invade their privacy with different levels of software. It was a different kind of source that was working towards a solution, not really an argument paper.

Paton-Simpson, E. (2000). Privacy and the Reasonable Paranoid: The Protection of Privacy in Public Places. The University of Toronto Law Journal, 50(3), 305-346. doi:10.2307/825907

This article is focused more on privacy in general and in public spaces and what has been done in response to people’s concerns. There is also an analysis about to what extent the risks related to privacy are. In general, it’s understood that people who go outside will be prone to their persons and any accompanying information being followed. It has been brought up that with the technology these days, it’s impossible to know exactly how specific people can be observing you in public. There are several examples of each concept that is described in this article which help describe what exactly the feature that is being spotlighted how it has had an effect in public. This structure helps to credit each factor of privacy that is mentioned because it’s an example that there have been issues with are being addressed. The examples help provide a scenario in which privacy was infringed upon, how exactly the government responded (if they deemed the case busy enough to reach their level) and the end results for both parties, most of which these cases have not been facing any repercussions because in public space people give up a little of their privacy so these acts are not considered aggressive enough. This citation seems very reliable because it is a published journal. It also has several footnotes on every page which shows that the information taken was from reliable sources and it is the not the author’s own opinion, but outside sources pulled together comprehensively. This source showcases both sides of an argument, one side is more along the lines of the bad parts of how privacy is invaded in public but also shows the opposing side of how if people expect to be protected in public, they must know that some of their privacy will be lost. This paper is a little bit more general as it talks about the concept of privacy and on a little bit of a broader scope, how there are certain risks, how the paper is more centered for those who want to know what exactly is encompassing them when they are being watched in public. I don’t believe that this research will directly impact my subject as it is does not really address the topic of ride-sharing, it’s just referring to the topic of privacy in general. It does help with background and being in public spaces, what are certain features that people look out for when dealing with this topic and themselves.

Pingley, Aniket, Wei Yu, Nan Zhang, Xinwen Fu and Wei Zhao. 2012. "A Context-Aware Scheme for Privacy-Preserving Location-Based Services." Computer Networks 56(11):2551-2568 ( https://search.proquest.com/docview/1081859323?accountid=14496 ). doi: http://dx.doi.org/10.1016/j.comnet.2012.03.022.

This source talks about how with location sharing services there is a need to address privacy protection while still maintaining high accuracy in location pinpointing. Just like how in online transactions there is a third party or a secure form of transaction, location sharing services cannot follow this same standard. The amount of protection has to be catered differently than another application because of the real time location aspect. Factors are always changing on the road in real time so it cannot accurately update if it is limited to what data it is able to access. However, someone’s privacy could be in danger because of the app’s current tracking of the user as well as tracing an IP address so the user doesn’t even have to voluntarily input information yet they are still being tracked. The paper introduces a solution for these issues which is a system that helps with both data privacy and user anonymity. The solution is a program that sort of creates a noise distribution so a user’s certain location is offset. It is basically putting the location of the user through some encryption and reporting that location that only the system knows how to read, so it is not manipulating the actual location, but just how that data is input into the system. This resource is reliable and actually very helpful because this solution has already actually been implemented into two major operating systems, Mac OS and Linux. This is proof that this solution did in fact help with masking locations but also still being accurate. There are several amounts of data to back this up as the research has been proven and been implemented by large name brands. The source is not biased, it is showing the findings of a solution software that was proposed, so there is no one side being taken. The targeted audience would be those who are suspicious of using these softwares because of the fear of their privacy being invaded or potentially data being stolen, but this software has proven that it can handle securing data as well as keeping the user anonymous. This source changed my way of thinking in that it is possible for there to be software that will help protect the issues that people have with this. Essentially, this resource is very helpful to my topic because it is one instance of a solution that actually exists that directly answers the issue of my topic.

Piza, E., Caplan, J., & Kennedy, L. (2014). Analyzing the Influence of Micro-Level Factors on CCTV Camera Effect. Journal of Quantitative Criminology, 30(2), 237-264. Retrieved from http://www.jstor.org.libproxy.berkeley.edu/stable/43551989

This article talks about CCTV and how its ability to stop crime is inconclusive, so it goes into the different aspects of CCTV, what it measures, how it works, and how effective they were on trying to capture a different aspect of a crime scene, and it will circle back to offer solutions on how to improve CCTV so they can best be maximized for what they were made to do. Initially, the article starts with CCTV and how it works, what are the aspects that make it up, such as line-of-sight or ability to target crime as the scenery. There is mention about how the CCTV works and what steps have already been made in order to advanced the capabilities of the CCTV. Then specifically, there was mention about the project of CCTV in Newark and how this specific experiment had certain results, such as there was a crime reduction in one experiment. There is also a lot of variation because this source takes in completely separate focuses of CCTV and breaks them down each into their own section such as separating environmental factors and line-of-sight, which are two features of CCTV that could go together because they can directly influence one another. The source has several references as well as including many statistics as back up for its claims. There are also several footnotes which seem reliable enough to trust for backing up the main paragraphs. There are also a lot of photographs that appear to have been taken by the CCTV which provide strong evidence in favor of CCTV’s adjustments. There was also some tables that could be analyzed in order to understand some data on how CCTVs have been effective, but in paragraph form, some of the data was hard to interpret because there was jargon. The numbers were not super clear if they were good or bad and it was not listed how the numerical data was significant to the original argument, but it did analyze the findings. It was also concluded that there are several natural challenges that surfaced with this technology.

Shin-Yan Chiou, & Yi-Cheng Chen. (2014). A Mobile, Dynamic, and Privacy-Preserving Matching System for Car and Taxi Pools. Mathematical Problems in Engineering, 1–10. https://doi-org.libproxy.berkeley.edu/10.1155/2014/579031

This article has a point about how carpooling has gained a more technical approach and the main focus in on a dynamic method for matching those who use the app on an android mobile devices as well as preserve the user information. The article starts off by introducing the idea of ride sharing. In recent years, an increase in technology has lead to an increase in car sharing and different pool services including cloud computing technologies to provide insight about why these technologies have proven useful to developing these services. There is some detail about what algorithms go inside these apps and several graphs and diagrams to demonstrate how the software works, including how the matching system works and what factors it takes in or the probabilities that a certain match is called. There is also a diagram to show how the application works as well as steps that show how well it works. This paper mostly focuses on one specific app and showing that there are several security measures taken in order to prevent information from leaking. The audience for this piece are those who are current users of ride sharing apps who have the potential to feel like their privacy is being compromised therefore this paper suggests a solution to a new app that would have very similar features to being run but would have that additional security feature that is wanted. This source does not take an argument as it is more of a descriptive passage where an app is being described and its features are being up played. There seems to be a little bit of a subjective point of view because the paper mentions that this app can solve all the issues of privacy that other apps are having troubles with but they do not have the validation to prove that about other apps. The reading was a little bit difficult in this reading because there were several math equations located in the bottom part because there was a system analysis section. Some of the variables are hard to follow even though there is a lot of explanation behind it. This source is very relevant to my paper because it shows that people have decided to think of an alternative app because of the concern that information is being leaked in already existing ride sharing apps that input personal user data. Although it is not directly supporting my research, it does provide data that needs to be interpreted and an argument can be formulated using this article as textual supporting evidence.

Thomas, C. (n.d.). Retrieved from https://libproxy.berkeley.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3dasu%26AN%3d128646546%26site%3deds-livef

This article is about several issues regarding inappropriate geo-tracking and how there are self-regulated standards inputted in order for applications to not abuse the information they are given, but because there is voluntary user input, the online platform cannot sufficiently protect user information. There is mention about how Europe takes a lot more into consideration about people’s privacy than America in terms of government intervention. There is a suggestion about how the Federal Trade Commission can use standards from the Federal Communications Commission to create their own which would help companies determine stronger privacy protection for people. There is mention about several policies that are enact now that are meant to protect different aspects of human privacy. There is then an analysis of laws that the EU has formed. Then, it goes back into a broader perspective of what is defined as privacy but then specifies problems specifically with Uber and then uses this to specify that autonomous cars could still face this issue. There is then government related information including how governments have access to this data as well indirectly from companies who use this information for company changes as well as how this relates to the Fourth Amendment which has manipulated how privacy can be accessed. The FTC guidelines are then discussed and in what ways it is effective and not and how the FCC and other state laws can benefit from using those standards. A solution is then proposed for ride sharing platforms including what should be asked from the user, to what extent the government is allowed to interfere, etc. The paper wraps up with statements about how it is expected the main audience for data breaching is the government and how there are several laws now to help ride sharing customers be protected from those who want their personal information. This source seems reliable because there are several references to acts that the government implemented with properly labelled footnotes. I would recommend this source because it goes very into detail about people who give up their information to these ride-sharing applications but don’t know what information they are giving up and to what extent the government might exploit this information. This piece helps to inform them of what government measures have been taken to ensure that their data is safe. This piece is very helpful for my topic because it goes into the government side that has had to be tamed and shows what is currently in place to address these issues. This hasn’t really changed how I think about my topic because it was already very clear that the government had insights into personal information but I now know about the measures that have already been taken in order to constrain the freedom they have to accessing this data.

Wang, Yu, Shanyong Wang, Jing Wang, Jiuchang Wei and Chenglin Wang. 2018. "An Empirical Study of Consumers’ Intention to use Ride-Sharing Services: Using an Extended Technology Acceptance Model." Transportation:1-19 ( https://search.proquest.com/docview/2046926304?accountid=14496 ). doi: http://dx.doi.org/10.1007/s11116-018-9893-4.

This study is talking about how ride-sharing has already defined itself as being a form of transportation. This paper approaches how selected customer intake of data can help ride-sharing services gain traction. There were surveys taken from participants and conclusions drawn upon their data about different aspects of the model. The paper starts with just setting background as to what ride-sharing is and what are reasons they have come to exist in today’s society, what benefits they offer. There is some mention about China and their government and how they utilize ride-sharing in a different perspective than Americans. The next main section is the research that was done and how it was set up, using a framework called Technology acceptance model, which is not just pertinent to seeing how effective of a technology ride-sharing is. The results of this framework don’t go that far into the privacy sector, but it is mentioned that privacy is one among many concerns with this technology. It is rather aiming towards how people are reacting to this technology as a whole, what factors they think are being affected, etc. A little bit of background is given about the data collection method and the results are also discussed. The conclusions this paper draws is that ride-sharing has several good things, including its effect on the earth, and related to the customer, there are several more aspects that are positive such as usefulness and awareness that are highlighted by this technology. There is only a small part dedicated to the fears that people have about security risks. However, the pros heavily outweigh the cons as concluded by the survey. There are some suggested solutions after the conclusion to show how to reach the “trial” stage of marketing because they are past awareness, but need this extra boost to really take in and turn the person into a customer as well as measures to be taken in order to strengthen security. There is also lastly a small footnote about how this data is not entirely representative of the entirety of those who are interested in or use ride-sharing services, and several solutions are offered to make this research, if conducted again, done differently to gain more effective results. This resource seems reliable because there are plenty in-text citations. There is basically a citation every two sentences if not closer. There are also several diagrams and tables that are used to describe the strategies that were utilized as well as the results of the research. The audience are those have already been aware of these services, but there are solutions being offered as to how to make this more appealing to consumers. I think that this piece will contribute to my paper because it is proving the point that there can be positives that come out of this, and even though the paper focuses more on solutions on how to gain more profitability out of this growing technology, it does address the past issues.

Zhou, Tao. 2016. "The Effect of Perceived Justice on LBS Users' Privacy Concern."Information Development 32(5):1730-1740 ( https://search.proquest.com/docview/1824751209?accountid=14496 ). doi: http://dx.doi.org/10.1177/0266666915622980.

This resource is summarizing how with the rise of location-based services, there is a huge concern about privacy which harms if people decide to continue using the application or not. There are three factors that are considered when looking at someone’s own privacy and how they might be breached as well as if they continue to use or not based on the information they receive. Very recently China ahs has for several mobile services, but the cost of retaining someone in this industry in that country versus finding a new person to experiment is costly since the emphasis on technology does not hold the same as the United States. This source helps with showing that because of the data collection it comes up as a factor that people do not enjoy because they do not know if the applications they put their information into are trustworthy. This paper’s purpose was to specifically see if people’s preference in how much privacy they allow for this app to have access to, if they respond to them in different scenarios. The privacy concern used perceived justice as the best way to get customers to trust their services, which is basically providing terms that seem fair to the user so they are more likely to input their personal data. The paper does research about the level of interaction with customers and a combination of different levels of satisfaction, app application, and policies to see which the customers respond best to, which was just that with perceived justice creates the most customer satisfaction and thus retention. This source is useful and reliable because it is a case study that was done in  order to figure out what method that apps can use to target users that have the most retention rate without being too intrusive. I would definitely recommend this source to applications who seem to be having trouble retain customers because this is the best approach to addressing the privacy issues. They can never really be completely avoided, so it is best to handle them head on because that also will show users that the application is informed. This source definitely provides an outside optimistic perspective on figuring out ways around the issues of user privacy because it acknowledges that there are going to be potential problems and works towards finding a comprehensive solution.



Ride-Sharing Privacy
Ride-sharing is defined as multiple persons, not related to one another, using the same transportation, typically a car, to reach their respective destinations. People can share rides on a short notice, which increases the efficiency of travel. Most often, the riders are not related to one another, and the shared vehicle will eventually reach each rider's destination, as they are in close enough proximity that traveling together is efficient. Ride-share platforms offer a platform where drivers and riders can connect, agree on a pre-determined price calculated by the application, wait time, and location of driver, essentially a way to contact their driver and gain travel information without having to release personal information. Ride-sharing is different than carpooling because the main objective of carpooling is that the driver most likely related to those who are receiving the ride and are purposely recruited for the benefit of the shared parties. Additionally, ride-sharing is mainly hailed through mobile applications, something that sets it apart from normal carpooling, which is primarily set up based on people who already know one another.

Ride-sharing is primarily accessed through a mobile application, and because of this, there are several dangers that could lead to an infringement of the user's privacy and their personal information. Mostly, ride-sharing privacy is relevant to a user's location because of the app's ability to pinpoint in live time a user's position. Ride sharing applications primarily use location-based services (LBS) in order to be able to trace the user's location. With location sharing services, there is a need to address privacy protection while still maintaining high accuracy in location pinpointing. Unlike how in online transactions there is a third party or some sort of secure form of transaction, location sharing services cannot follow this same standard. Someone’s privacy could also be in danger because of the ride-share applications' current tracking of the user's location or tracing an IP address so the user does not even have to voluntarily input information about their location, yet they are still being tracked. Additionally, if the user data of locations they interact with falls into the wrong hands, a potential abuse of the data whether that be creating an online profile based on cumulative data of the individual or companies able to share personal information around multiple sources could arise.

There have been several proposed solutions to the applications in order to try and alter the side-effects of LBS. The amount of protection has to be catered differently than another application because of the real time location aspect. Factors are always changing in real time, so these services cannot accurately update if it is limited to what data it is able to access, but they are good starts being able to try and eliminate these issues in the future.

History
Ride-sharing as a concept has been around since World War II. It wasn't until around 1990s when programs were starting to digitalize, although the concept had long been established since. Some of the first telephone-based ride-matching programs were Bellevue Smart Traveler from The University of Washington, Los Angeles Smart Traveler from Los Angeles's Commuter Transportation Services, and Rideshare Express from Sacramento Rideshare. However, in these telephone-based programs the operational costs started exceeding their revenues and an alternative, internet and email driven ride-matches, was proposed. This program was tested on a closed campus, and it was only available to University of Washington related people, which proved highly successful. Two other programs, ATHENA and MINERVA were both computerized but faced unsuccessful endings. *additional citation* When the internet was created in the 1990s, online ride-matching was created. Websites originally had lists or forums that people could get information for carpooling options from, but the internet provided the ability to develop platforms, which were more dynamic and interactive. Yet, this concept did not kick-start because the mechanics were not any different than traditional carpooling, only the ability to find them had been made easier. Since carpooling and ride-sharing were not a very popular option, the smaller population who did participate already had set agendas so timing wise it was not helpful to those who needed transportation outside of a regular workday commute. Larger scale companies started becoming interested in partnering with ride-matching companies in order to spread the ride-sharing platform which are gaining more traction as availability of mobile technology and thus accessibility not from a stationary point is becoming more prominent.

User Input Features
Ride-sharing applications have several user input features:


 * Users can input their pick-up destination.
 * Users can input their drop-off destination.
 * Users can save a home or work address.
 * Users can save unique places if they are visited frequently.
 * Users can also pinpoint their exact location on a map.
 * Users can save their credit card information for easy access.
 * Users can invite their friends which the app pulls from their phone contact information.
 * Users can create their own profile.
 * Users can see the profiles of their potential drivers as well as any reviews that come with it.

Ride-sharing companies also have several tracking features that are unclear in terms of what user information is being collected:


 * The application automatically connects and tracks the user's current location and surrounding areas, so when the app opens, an accurate map is immediately opened as the home page and the location of the user are immediately tracked.
 * Recent addresses that have been set as either pick-up or drop-off locations are in kept in the search history.
 * Letting the app connect to personal data that is stored in the phone, such as access to contacts, can let the app access more than just phone numbers (addresses, personal information) which have been stored under the contact in the phone.

Uber Privacy
Uber has an option where user privacy can potentially be forgotten and they are aware of what data they are collecting from the user and are being transparent *citation*:


 * Ability to share or un-share live location as well as having location settings always on.
 * Ability to receive notifications about your account and trip.
 * Ability to remove stored contacts which adds on another way that can link two people together if someone is tracking someone's information.
 * Ability to share trip details with 911 in case of emergency.
 * Ability to sync personal calendar with the app.

Camera inside the car
Very recently has the presence of physical cameras been implemented in ride-share vehicles. Prior to this, the only time cameras were related to cars were traffic cameras and police cars. However, there has been a rise in the amount of continuous-recording cameras that are not just surveilling the road and keeping track of what happens outside the car. The implementation of cameras inside cars to record interactions between drivers and riders is something new. However, people are concerned about their privacy because this recording goes on during their trip duration, and they do not verbally consent to their recording. However, they consent to being in a person's car, hence they must abide to the driver's rules. There are federal rules about audio recordings, federal laws only requires "one party consent". *citation*

Government policies about recording
According to the Omnibus Crime Control and Safe Streets Act of 1968, there are policies regarding recording audio conversations, including clarifications about the "one-party consent" rule that comes with it. Regarding audio conversations, it is illegal to record a conversation for which one is not partaking in. However, they are allowed to record if they are a member of the conversation themselves, without having to receive consent from the other party or having to let them know there is recording happening.



The potential abuse of location-tracking
There are several areas where data could potentially be abused by the application knowing the rider's location. Since trip data is collected, if the ride-sharing company has partnerships with corporations, their partners can use the data to predict future locations and be able to pinpoint an individual's interests and market towards them. *citation* Corporations can collect information on what types of stores and what brands are most often visited by a user and can build an online profile, which is traceable. This can also relate to advertising companies, which can target personal interests and alter their online interactions to start showing ads that are catered and specific towards where the user has visited. *citation*

There are some cases where bad implications could arise. If the user were to partake in something related to their political standpoints, companies can store this for later information and potentially use it against the user if they come into contact with the company in a professional setting. This can apply to medicinal, religious, or legal affiliations as well, that a user's location and places visited cannot be justified when being looked at from an outside perspective.

Relating more to the online profile created of the user, if a person solely relies on ride-sharing services to get around, one can track how long the user has been away from their home and how far away they are from their home. This becomes an opportunity for people to stalk or rob the user because they know when is the ideal time people aren't home. *citation* Looking on a broader scale, based on the demographics of the area a user interacts with, if they frequently visit the same stores within a certain area, information can be assumed, such as estimated income. *citation*

Users have the option to save a home or work address for easy access. Most often, users put their actual address, but in some cases, users have been known to put an address a couple streets away, just for their safety in case data gets leaked. However, while this is a very basic level of deflection, putting a home address a couple streets away still gives a general location of where the user is stationed.

Location aware applications
Individuals have concerns over how, what, when, and where their location information is being stored as well as to what extent others have access to it. Not only pertaining to ride-sharing applications, but any applications that have sharing enabled of sorts, there are several types of applications that are location aware. Location based searching (LBS) occurs when a user's tracking returns items and buildings around the user's current location in order to be tracked. A map is drawn with the orientation of the surrounding buildings to determine a location. Geo-location services are having the user tracked with an environmental footprint. It's an estimate of a user's location. Mobile sensing is the process of pinpointing the user's physical device, which has sensors and information that can be collected. Location sharing is a voluntary state where the user is in live-time and their location is constantly being updated and tracked.

Making use of user information
Looking more at the applications and how a user accesses the ride-sharing service, once a user inputs data into the app, it will be accessible on the web forever. Even if they delete information or delete their account, the information has been created on an online platform and now exists whether the user consents to it or not. These applications ask for user information such as phone number, email, and profile picture, all features which can be used to trace back to the user's identity. Once this information is in the application's database, it can accessed by the application as well as indirectly by any partners of the app.

Most apps have the payment charged and completed before a user can be connected to their ride. Users have the option to store credit card information for easy access instead of having to repeatedly input payment information. While there is an added level of security, such as passcode or touch ID before every transaction, this does not ensure the safety of this information in the app. It only ensures that the current transaction is made under the consent of the user.

Reverse image search
Users are allowed to input a profile picture into their applications. Doing so has the intention of helping drivers spot their intended riders. However, this can cause an issue because if somehow a rider's image is saved and uploaded to the web, connections can be made to personal accounts. For example, with Facebook's face recognition advanced algorithm, it is easier to identify people's identities from outside pictures.

Targets
There are three main categories where location-based services should be protecting:


 * 1) Identity protection - Location-based services can put together an identity of a user, even with anonymous identification, through the frequency in locations.
 * 2) Location protection - Very straightforward, the user's true location should be protected. There is no absolute way for a person to completely hide their whereabouts.
 * 3) Behavior protection - The goal of this protection is to survey the mobile patterns from the user's behavior, what locations they attend that people can interpret their behavior and make judgments about their character.

Noise distribution
Researchers have come up with a conclusion which introduces a solution for these issues which is a system that helps with both data privacy and user anonymity. The solution is a program that creates a noise distribution so a user’s certain location is offset. It is basically putting the location of the user through some encryption and reporting that location that only the system knows how to read, so it is not manipulating the actual location, but just how that data is input into the system. This solution has already been implemented into two major operating systems, Mac OS and Linux. This solution helps with those who are suspicious of using these ride-sharing application softwares because of the fear of their privacy being invaded or potentially data being stolen, but this software has proven that it can handle securing data as well as keeping the user anonymous. It is more like an extra layer of security that creates another blanket to hide the user.

K-anonymity
K-anonymity serves as an Anonymizing Server, which is a trusted third party server which is in charge of providing anonymous cover for users. K-anonymity is used to preserve the location privacy by creating a location cloak without knowing the actual location of the user. The software attempts to find a number of users close to the actual users because then exact locations could not be correlated back to the original user in question and these several locations which cannot be identified to the users in close proximity would protect the original user. There is no way to distinguish between all the users.

Fuzzy interference systems
Another solution is to try and use fuzzy interference systems when relating to mobile geo-services. This solution would use different details to identify the user that would not be prone to organizations abusing the obtained information. Currently, location based services can reveal several sensitive pieces of information, like closest religious institutions, which can reveal the identity of the user, which organizations utilize for purely commercial purposes. The paper proposes a solution, anonymization, which protects user’s data in case of accidental breaches. There is an explanation of the fuzzy inference system and how it works *explain how it works* and then the potential implication method in taxi drivers to see if this is an effective way of protecting people’s information because there isn’t a concrete design with anonymization that has proven to do well. There are different levels of precision that the location system can narrow down on a user. These systems turn quantitative data into qualitative data which would obscure a user’s identity and location. After a trial implementation with taxi drivers, several complications came up, mostly human misinterpretation, but in the future, investing more time into this solution and combining it with already existing solutions could provide a more effective solution. To those who are afraid of their locations being tracked and that being used to trace back to the user, this solution makes user data fuzzy so if they are being tracking, it is not completely precise. There are data tables that show experimental distances of how close a tracking software was to those who had implemented the fuzzy solution. This solution takes on a different approach because it doesn’t entirely solve the problem of how to entirely protect the user's privacy, but it is working towards it since the solution has not had enough time to mature, as it is just in introductory stages. It sheds light on the fact that the location tracking software is still not private even when solutions have been taken to try and overcome this solution but leaves an open ending because it ends that with more research and resources put into it (and specifically told what areas could be developed better) it could expand further and be developed better.

Location transformation
One proposed solution is a model that would estimate how difficult it would be for outside sources to get their hands on someone’s private information. There are several mechanisms proposed that would be helpful in hiding data including location obfuscation, perturbation, confusion and suppression, and cryptographic techniques.

Location obfuscation
Obfuscating a user's location means to cloud the user's location. A user's location coordinates are still being preserved, however the accuracy is just being degraded. However, this cannot be a complete solution because this would just neglect the entire reason of location-based services. So being selective in what an application is obfuscating, would help with protection.

There is a program, called NRand algorithm, which is the algorithm that determines the amount of obstruction that is put on the user location data. There are a couple issues that arise with this algorithm, including determining how much noise should be implemented and if the changing of the data is enough to alter it to an unrecognizable form from its original state.

Location perturbation
On a map, a location locks onto something in close proximity but not the exact user location because of added noise. With this added layer, if there is another location in a close enough range, a transition will be added to multiple locations and mask all points of interest.

Confusion and suppression
A dummy location is set as the true location. This is done so by pinpointing a user's specific location and transforming it into several other locations, yet keeping the true location. Suppression is a subset of these different applications where for a short period of time, when a user enters an area, the user information is temporarily suspended and the identity of the user is lost, so when they exit back out of the protected area, they have a new identity.

Cryptographic techniques
Original data is unable to be tracked because information goes through some sort of cryptographic interpreter, could be transformed into several different data points.

Tommytheprius Week 10 Peer Review
Lead section:


 * The tense of your first sentence sounds a little strange. You could rephrase to say "Ride-sharing is defined as multiple persons, not related to one another, using the same transportation, typically a car, to reach their respective destinations."
 * When you say that drivers and riders "agree on a price" it seems misleading. Don't apps always calculate the fare for both parties? This sort of suggests that there is room for bargaining. I'd either cite that statement or take it out.
 * Do you mean "live" instead of "life" in this sentence?: Mostly, ride-sharing privacy is relevant to a user's location because of the app's ability to pinpoint in life time a user's position.
 * In the sentence "Unlike how in online transactions there is a third party or some sort of secure form of transaction, location sharing services cannot follow this same standard." it seems like you should add a citation or add in facts about why they cannot follow this same standard
 * I'd add a citation to the sentence "Additionally, if the user data of locations they interact with falls into the wrong hands, it could result in abuse of the data whether that be creating an online profile based on cumulative data of the individual or companies able to share personal information around multiple sources." because the repeated use of the word "could" makes it seem subjective.

History:


 * Unless you are planning on providing a history on each of the bulleted companies, I would recommend taking out that list because it looks odd.
 * I feel like something to work on in this section is the encyclopedic tone. You use phrases like "did not really take off" and "carpooling and ride-sharing were not a very popular option" which make your statements seem wishy washy. If you take out words like "really" and "very" it will seem more like fact and not your own views.
 * I also think you might want to add in a few more citations to this section because it looks a little sparse.

User input:


 * In the sentence "They also have several tracking features that are not clear in terms of what information is being tracked from the user:" would it make more sense to say "Ride-sharing companies also have several tracking features that are unclear in terms of what user information is being collected"?
 * I like that you have a section on Uber privacy, but since Lyft is their main competitor, should you also include a Lyft privacy subsection?
 * The sentence "Very recently have the need for physical cameras been implemented." seems worded a little awkwardly. You could rephrase to say "Very recently has the presence of physical cameras been implemented in ride-share vehicles."
 * I like this section overall, but there are no citations in it at all which is concerning. The sentence "However, people are concerned about their privacy because this recording goes on during their trip duration, and they do not verbally consent to their recording." seems like it really needs a citation because this could be seen as your own interpretation.

Concerns:


 * In the sentence "Going along with how corporations can see where people have gone, there are some cases where bad implications could arise, such as if the user were to partake in something related to their political standpoints, companies can store this for later information and potentially use it against the user if they come into contact with the company in a professional setting." I think you should consider removing the "Going along with how corporations can see where people have gone" part because it reads sort of like an essay this way and like it is trying to hammer down a point of view. You can also split it into two sentences with the period after "arise" and starting the new sentence with "if".
 * add citation for this sentence: Individuals have concerns over how, what, when, and where their location information is being stored as well as to what extent others have access to it.
 * The tense in the sentence "Location Sharing is a voluntary state where the user is in live-time, constantly updated state of being tracked." seems off. Should it be "Location sharing is a voluntary state where the user is in live-time and their location is constantly being updated and tracked."
 * The last sentence of the "reverse image search" is unfinished

Targets:


 * This section seems appropriate for bullets. I'd add a colon after the first sentence and then bullet the three things

Solutions:


 * Instead of saying "this paper" then citing the paper, you could say something like "Researchers have studied..." and then citing at the end of the sentence.
 * In the K-anonymity you could maybe explain what the K is for?
 * I'm confused on the "fuzzy systems" line... are you going to add more?
 * Saying "one source" in location transformation seems odd and not quite encyclopedic. You could say something like "One proposed a solution is..."
 * The sentence "Obfuscating a user's location can cloud the user's location." seems repetitive. Obfuscating and clouding are synonyms.

Overall notes:

I think you've got a really good article here. The main things I noticed were a lack of citations and some instances where the tone didn't seem very encyclopedic (especially when you discussed individual papers, which I know can be tricky because you're probably taking directly from annotations). Also, I feel like the see also section should be solely hyperlinks, so if the two unlinked terms right now don't have wikipedia pages, I'd consider removing them or replacing them with some relevant terms that do have hyperlinks. I also added a couple hyperlinks, but you could definitely add more since there don't seem to be many. Finally, the wikipedia guidelines are to only capitalize the first letter of a title or subtitle, so I did some copy editing for that. You got this!

Tommytheprius peer review
I like what you have in your lead section so far, but there is no mention of privacy, so that's something I would think about including. In the "History and development of ride-sharing apps" section I assume you will be adding info to each of the bullets, but I would also hyperlink to the wikipedia pages of all of those companies. In the software subsection of the "User input/privacy with software data" section, I think consolidating the bullets into paragraphs and explaining them would make it a little easier to read and understand, which I assume you were planning on doing anyway. In terms of balance when thinking about the structure of your article, the hardware section seems a lot smaller than the software section, but that may be because there's simply less information about it. Also, the placement of "Government Policies about Recording" seems a little weird in that section since there's nothing else about laws within it. You could think about creating a legal section if you had other laws you wanted to mention eventually. Again, I assume you were planning on doing this but I think making the bullets of the "Places for security breaches" section into paragraph form and explaining them more would help with readability. For the See Also at the end, I think those are supposed to all be hyperlinks to other wikipedia pages?

Overall, I think you've got a solid start here. I especially like where the "Places for security breaches" section is going. I think your tone is very neutral and unbiased. My main suggestions are to add in a discussion of privacy in the lead section, to consolidate bullet points into paragraphs, and to add citations and hyperlinks (again, I know you were intending on doing this eventually). Good work!

Week 10 Peer Review: I fixed a lot of things in here that were suggested because sometimes my wording is off. I write an idea down but cannot think of good wording at the time and so it comes off as repetitive or just not making sense. I fixed some of the formatting and some of my word choices because they didn't make sense. I replaced a bunch of the sentences that were copy/edited because of tense fixture or just sentence structure. I will add more citations as well, because some of my information seems to not be subjective and needs a citation to be credible. I will go through and also try and hyperlink more things which I don't really have because there's mainly just common language used. Going through the tone again might be helpful too just to make sure there aren't words like "very" which take away from the encyclopedic tone.

Angryflyingdolphins peer review
I like the lead section as it gives a good overview of what subtopics your article will explore. However, there is no mention of privacy in the lead section which may make your article seem like a page on just ride sharing. You should also change the wording and sentence structure in the second paragraph of your lead section. I assume that your "History and development of ride-sharing apps" section is a work in progress but you can still add some hyperlinks to the company names. Your "User input/privacy with software data" section is too bullet heavy. I feel that all the bullets in each subsection can be put together to create a well-flowing paragraph. I think that the "Hardware" and "Government Policies about Recording" sections should not belong in the the "User input/privacy with software data" section since they do not seem relevant to software and could easily be their own larger sections. Wording in the two aforementioned sections could also use a bit of improvement. The bullet points provided in your "Places for security breaches" section seem a bit awkward since your title gives the impression that you're simply going to list places. The section could probably be edited into paragraphs. The "See also" section can be filled out with hyperlinks.

Your first draft is a good start. The "Hardware" section is pretty well developed and could possibly serve as an example of how to approach your other sections. Overall, nice work!

Week 6 Response to Peer Reviews: I wasn't sure how to exactly start the lead section, so it was helpful to point out how exactly I could differentiate between the page just being on ride-sharing vs the privacy of ride-sharing. Because of that, I created a section right under that was regarding privacy so it is apparent what the page will be on. I think that I might have to take a look at it again because I think it would be helpful for it to kind of reflect what ideas are targeted in the page. For both reviews, there was a request to change a bulleted section to a paragraph which I was able to add, but I have to go and add a citation back for it. The legal section I'm a little iffy about, I would like to try for expanding it more, I'm just not sure how related to the topic it is as well as if ride-sharing has had enough government related issues that it could be written about. I am getting around to links since I am finding more specific things about location sharing which is helping me get into the more detailed portions of my page. I will attempt to get rid of the bullet points in the user input/privacy section but I was intending for it to be less factual and just a list of what are all the entrances for data because they're not meant to be analytical, just informative. I think the hardware section was a little bit better than the rest because that's what I originally wanted my whole page on but could not find as many resources for it.

Midwestmich99 peer review
I think the information you have in your lead section so far is descriptive and easy to follow. To build on the lead section, I suggest mentioning some of the other topics in your article, such as “Places for security breaches”. This way the reader knows what to expect in the rest of the article.

The information in your article is well balanced. I didn’t feel like one section overpowered any of the other sections. I thought the structure of your article was clear and easy to follow. The only part I was a little confused about was the “Uber Privacy” in the Software section. I feel like this section could be highlighted somewhere else, because this is a specific example of “Software”. You could also explain that this a specific example of ride-sharing software, and the privacy options within that software. Adding a transition sentences will help the reader understand how each section relates to each other.

A really minor change could be making the “Place for security breaches” heading more specific. I was a little confused by this title, because I thought you meant physical locations where security can be breached. Naming it something more specific like “Potential information that can be compromised from ride sharing” can help the reader understand what you're discussing.

The tone of the article was unbiased. You do a great job of presenting the information in a factual unbiased way. Overall, I think the information provided in your article is very interesting!

Week 7 Response to Peer Reviews: I need to revise my lead section. Just not clear on how specific I should go into what the entire page is about because it should be brief and not repetitive. Most likely I'll take out the part on Uber because it's too specific and there's nothing that one company has specifically specially done in response to this. After going to lab too, I have a better idea of how to expand on each of the sections as well as if I should add/clarify my topics or sections because they were not clear enough at the beginning. I fixed a couple of the headings just to make them better.

MY's Peer Review for Week 8
Good Job! I can see that you added a lot of new things compared to last week. Here are some revision that I made and some advice I can give:

1. You can try to add more citations and hyperlinks. It feels that you have completed most of your articles, but the reference part only has 3 sources, so it’s a little hard to confirm the credibility. Try to add more sources and hyperlinks next week, so the readers know where your arguments are from.

2. In “government politics about recording” part, you mention some laws that govern the general recording, but it’s not specially related to the camera inside the car/ride-sharing privacy. You could provide an example of how one specific law could be used on this aspect, so it’s better related to your topic.

3. I fixed some grammar/spacing mistakes, deleted some oral expression and also changed a few sub-headings that I feel a little broad/confusing, you can check it. It’s totally fine if you want to change back!

4. In the lead section, you only introduced what ride-sharing is, and then used another sub-heading to take about the privacy issue. But since your topic is ride-sharing privacy, it could be better if you mention the privacy aspect in the first one or two paragraphs, so the readers know it on the first glance~

5. I really like the weak points part! Some bad implication of location-tracking is really insightful for me. I didn’t think about that my data on ride-sharing apps might be used in these ways. You mention a lot of possibility here, but is there any real-world example you can add onto this part? For example, someone put their home information on the app, and then he got robbed? You can include some of it if you can find any!

6. In the “Targets” part, there is one sentence “Very straightforward, the user's true location should be protected. There is no absolute way for a person to completely hide their whereabouts.” I personally feel that the tone is a little bit absolute when I read it. You can try to make it more encyclopedic.

In all, great job! It’s really easy to understand your ideas, and the use of bullet points make my reading experience much better! Keep going, we’re almost there!

Week 8 Response to Peer Review: I still need to add more citations. I realize that at the beginning of my annotations I couldn’t really find sources that were relevant to helping build the background of my topic, so I just kind of wrote based on my own knowledge and what I read from sources, but didn’t really put too much of the academic stuff in the front, which is why it’s a little light on the citations. I’ll add more though as I try and find sources just generally on the topic itself, not just privacy aspect. I talked a bit to Naniette who gave me ideas about what to look for on the legal side, so I’ll be branching out more for that. Also talked to her about combining my lead section so it’s not confusing. I was looking into court cases about LBS related issues, which some to many of the ones I found were not huge issues, but I can try and include them. I will also go through the whole thing and check for things like tone because I haven’t gotten around to that, I’ve just been writing, so I’m not sure if I sound a little bias in any areas.

Funfettiqueen Peer Review Week

Right off the bat, I notice that there are not many citations in the lead section and throughout the article. Even if it seems repetitive, I think it is safe practice to add a citation every sentence or so. In the first sentence, instead of writing "ride-sharing is defined as..." maybe just write "Ride-sharing is..." to make the sentence more clear/succinct. A potential rewrite could be, “Ride-sharing is when multiple people (unrelated to one another) use the same vehicle for transportation to reach a destination. Typically, the vehicle of use is a car.” Also, in the lead section, I am confused by "ride-share platforms". Are those just applications? If so, the sentence “Ride-share platforms offer a platform...” is a bit redundant. I am also kind of confused by the sentence “Ride-share platforms offer a platform where drivers and riders can connect, agree on a price, wait time, and location of driver, essentially a way to contact their driver and gain travel information without having to release personal information.[1]” In regards to grammar. I was also having a hard time following the sentence, "Ride-sharing is different than carpooling because the main objective of carpooling is that the driver most likely related to those who are receiving the ride and are purposely recruited for the benefit of the shared parties. “ In general, maybe take some time to break up sentences into other sentences rather than writing a long one to increase readability. In the sentence, "Mostly ride-sharing privacy is relevant to a user's location because of the app's ability to pinpoint in life time a user's position", I would change it to "most ride-sharing privacy concerns relate to a user's location...". The sentence structure is really confusing in the sentence, "However, these telephone-based programs the operational costs started exceeding their revenues and an alternative, internet and email driven ride-matches, was proposed." Additionally, for the history section, it might be a good idea to break up the large paragraphs into different, smaller sections so it reads more easily. In regards to the sentence, "They also have several tracking features that are not clear in terms of what information is being tracked from the user", maybe reword this as, “Ride-sharing applications also have several tracking features. However, it is not clear what information from the user is being collected.” Also, I am confused why there are bullet points to different ride-sharing apps in history. “ Uber has an option where user privacy can potentially be forgotten and they are aware of what data they are collecting from the user and are being transparent *citation*” I am confused about what this sentence means. I would also maybe think about hyper-linking location-based services if there is a page on that. In the "Making use of user information section", you make rather large statements that data will be stored forever. However, you do not cite any sources in this paragraph which might be hard to deem credible. Additionally, the sentence in "Reverse image source" is half written. For the targets paragraph, I would not do bullets but instead a full paragraph or subsection for identity, location, and behavior. Also, why is the section called targets? I am a little confused by this. What do you mean by it should be protecting? Noise distribution: you say “the paper”. What paper? Maybe this is just a copied and pasted annotation, but I wouldn’t refer to references in the article. Just simply write the sentence and then attach a citation. You also do something similar in “fuzzy interface systems” where you reference “the paper”. Additionally, it might be a good idea to hyper link obfuscation since it is a difficult topic to understand. Lastly, the sentence “Original data is unable to be tracked because information goes through some sort of cryptographic interpreter, could be transformed into several different data point” is a tad hard to understand. Despite these nit-picky revisions, your content and information is super good! I felt like you covered all relevant things related to ride-sharing and privacy and did a thorough job touching on these topics.

Week 9 Peer Review Response: I am working on adding citations to the lead section. Right now it kind of seems that most of my information is from my current knowledge. I will clarify because platforms does refer to the applications, I think I need to make sure I use the same diction because it can get confusing on what I’m referring to. I will take out the Uber part because it’s too specific and there isn’t really  a difference in the privacy between Uber and different apps (which I found out after doing some more research). I don’t know how I should write full paragraphs because for some things it’s like a list of functionalities that are self-explanatory and I don’t see what putting them in a paragraph what effect that would have. I will work on my wording because I leave a bunch of things unexplained.