Draft:Arash Habibi Lashkari

Arash Habibi Lashkari (born November 3, 1974) is an associate professor, educator, and author, professionally known for serving as a Canada Research Chair (CRC) in cybersecurity. He is currently an associate professor at York University and a senior member of the Institute of Electrical and Electronics Engineers (IEEE). He also serves as an adjunct professor in the Department of Computer Science at the University of New Brunswick.

He has been a lecturer for over two decades at several different institutions worldwide. He is also well-known as a pioneer in designing and producing Cybersecurity Datasets and open-source analyzers.

Education
Lashkari earned a Bachelor of Science in computer software engineering from Islamic Azad University 1995. Then, in 2008, he enrolled in the University of Malaya, where he completed his Master of Science in computer science. Later, in 2014, he earned his Ph.D. in computer science from the University of Technology Malaysia. He also earned a postdoctoral fellowship on cybersecurity from the University of New Brunswick and a postdoctoral research internship from Mitacs in 2016.

Academic services
Upon his departure to Canada in 2015, he joined the University of New Brunswick as a research associate in the Computer Science department, where he was later promoted to serve as an assistant professor and then associate professor. He is an adjunct professor at the Faculty of Computer Science, University of New Brunswick (UNB).

He is a senior member of IEEE and an associate professor at York University. Before this, he was also a research coordinator at the Canadian Institute for Cybersecurity (CIC). His research is centered on the modeling and detection of cyber threats, the study of malware, the security of big data, the analysis of internet traffic, and the production of cybersecurity datasets.undefined

Lashkari is a Canada Research Chair (CRC) in cybersecurity. His current work involves developing vulnerability detection technology to protect network systems against cyberattacks, as he has more than two decades of concurrent industrial and development experience in network, software, and computer security. He oversees many research and development teams at once, all of which are engaged in various projects, including the analysis of network traffic, malware, Honeynets, and threat hunting. He was responsible for designing the first cybersecurity Capture the Flag (CTF) competition for post-secondary students in Canada. He is also well-known as a pioneer in designing and producing Cybersecurity Datasets and open-source analyzers.

Research
Lashkari is among the most cited researchers in cybersecurity. He is well-recognized for his research in Malware Analysis and in several fields of cyber security, including Intrusion Detection Systems (IDS), Network Traffic, and dark web analysis.

Cybersecurity Datasets
These days, Machine Learning (ML) and Deep Learning (DL) techniques play a critical role in detecting serious cyber threats. A good dataset, on one side, helps train and create robust ML and DL systems and on the other side, supports research scholar in testing and evaluating their novel ideas to address various security problems. Lashkari was among the first and most famous researchers who generated and released more than 16 cybersecurity datasets since 2015 and designed and developed different detection and characterization solutions using ML and DL in different cybersecurity areas.

For Encrypted traffic analysis and characterization, he generated three datasets, namely VPN-NonVPN-2015, Tor-NonTor-2016, and Darknet-2020, and proposed DIDarknet: a Contemporary Approach to Detect and Characterize the Darknet Traffic using Deep Image Learning. In 2021, he proposed and developed a robust staking ensemble model for darknet traffic classification and characterization.

In 2016, he explored a lightweight approach to the detection and categorization of malicious URLs according to their attack type, including Spam, Phishing, Malware, and Defacement, and generated the ISCX-URL-2016 dataset; later in 2020, he designed the first DoH tunnel analyzer using Time-series classification and produced CIRA-CIC-DoHBrow-2020 dataset funded by the Canadian Internet Registration Authority. In 2021, he proposed a lightweight hybrid data exfiltration and malicious DNS traffic analysis collaboratively with Bell Canada.

From 2017 to 2020, he designed and developed three different Android malware analysis systems using ML and DL algorithms and proposed a systematic approach to generate the Android Malware datasets. He generated four datasets on the Android Malware analysis domain, including AAGM-2017, CIC-AndMal-2017, CIC-InvesAndMal-2019, and CCCS-CIC-AndMal-2020 along with proposing two new Deep Learning-based Android malware characterization solutions namely DIDroid and Entroplyzer collaboratively with the Canadian Centre for Cyber Security (CCCS). Also, he proposed a fast and robust ML-based intrusion detection and characterization system and generated CIC-IDS-2017 and, after that, extended the project supported by AWS and produced the first and only IDS datasets for Amazon, namely CSE-CIC-IDS-2018. He is the producer of the only available Distributed Denial of Service (DDoS) dataset, namely CIC-DDoS-2019, which covers 12 common DDoS attacks, including NTP, DNS, LDAP, MSSQL, NetBIOS, SNMP, SSDP, UDP, UDP-Lag, WebDDoS, SYN and TFTP.

Cybersecurity Open-source Analyzers
In 2015, he designed and developed ISCXFlowMeter as one of the first network traffic flow generators and analyzers, extracting 32 features from the network traffic on the fly. Later, in 2017, he expanded the analyzer and designed CICFlowMeter, which extracts more than 80 features in the fly.

From 2019 to 2020, he proposed and produced three versions of Android Application Analyzers for detecting and characterizing malicious behaviors on smartphones; the first version covers the data collection and static feature extraction, the second version focuses on developing a classification model using AI for static features, and the third version has the dynamic analysis module and related features to improve the AI-based classifier. In 2020, he designed and developed the first DoH analyzer, DoHLyzer, for encrypted DNS message analysis. In 2021, he introduced the first Memory Analyzer for ML and DL algorithms, VolMemLyzer.

Publications
He has authored more than 110 academic articles on various cybersecurity-related topics. He has also authored and contributed to books regarding cybersecurity, including;


 * Understanding Cybersecurity Management in Decentralized Finance: Challenges, Strategies, and Trends
 * Understanding Cybersecurity Law in Data Sovereignty and Digital Governance: An Overview from a Legal Perspectiveundefined
 * Understanding Cybersecurity Law and Digital Privacy
 * Understanding Cybersecurity Management in FinTech
 * Mobile Operating systems and Programming
 * Graphical User Authentication (GUA)

Selected Articles:

 * "Robust Stacking Ensemble Model For Darknet Traffic Classification Under Adversarial Settings," Hardhik Mohanty, Arousha Haghighian Roudsari, and Arash Lashkari, Computers & Security, Vol 120, 2022
 * "QKeyShield: A practical receiver-device-independent entanglement-swapping-based quantum key distribution, “Mohammaed Aldarwbi, Ali Ghorbani, and Arash Habibi Lashkari, IEEE Access, 2022
 * "Memory Forensics Tools: A Comparative Analysis," Mahdi Daghmehchi Firoozjaeia, Arash Habibi Lashkari, and Ali A. Ghorbanic, Journal of Cyber Security Technology, Volume 6, 2022, DOI: 10.1080/23742917.2022.2100036
 * "A memory-based game-theoretic defensive approach for digital forensic investigators," Saeed Shafiee Hasanabadi, Arash Habibi Lashkari, Ali A. Ghorbani, Forensic Science International: Digital Investigation, Volume 38, 2021
 * "KeyShield: A scalable and quantum-safe key management scheme," A Mohammed Y., AA Ghorbani, A Habibi Lashkari, IEEE Open Journal of the Communications Society, December 2020"A game-theoretic defensive approach for forensic investigators against rootkits," Saeed Shafiee Hasanabadi, Arash Habibi Lashkari, Ali A.Ghorbani, Forensic Science International: Digital Investigation, Volume 32, March 2020

Awards and honors

 * Bronze medal in the 13th Industrial and Technology Exhibition (INATEX) (Malaysia, 2012)
 * Bronze medal in the 14th Industrial and Technology Exhibition (INATEX) (Malaysia, 2013
 * Best of Security award in National APICTA (Malaysia, 2012)
 * Best of security in East Asia and gold medal winner in International APICTA (Brunei, 2012)
 * Two silver and two bronze medals in the 12th International Invention and Innovation Expo (MTE) (Malaysia, 2013)
 * Three silver and one bronze medals in the 24th International Invention, Innovation & Technology Exhibition (ITEX) (Malaysia, 2012)
 * The next 150 celebrating researchers who will shape Canada's future (Canada, 2017)
 * The Fredrik and Catherine Eaton Visitorship Awards from the University of New Brunswick (UNB), NB, Canada (Canada, 2019)
 * The Harrison McCain Foundation Young Scholar Award from the University of New Brunswick (UNB), NB, Canada (Canada, 2019) The Research and Academic Leadership Award, ICSIC, Toronto, ON, Canada (Canada, 2019) Teaching Innovation Award of the 2019-2020 academic year, University of New Brunswick (UNB), Fredericton, NB, Canada (Canada, 2020)
 * Gold medal in the Canadian Online Publishing Awards (COPA), on the Best Blog Column, Business Division for our "Understanding Canadian Cybersecurity Law" article series (Canada, 2021)
 * Became a senior member of the Institute of Electrical and Electronics Engineers (IEEE) (Canada, 2021)

Memberships
Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) in Computer Science (R7)

Recognition

 * Lashkari has earned 15 awards at international computer security competitions, including three gold awards, and was named one of Canada’s Top 150 Researchers for 2017.
 * Lashkari was awarded the University of New Brunswick’s prestigious Teaching Innovation Award in 2020 for his personally-created teaching methodology, the Think-Que-Cushion method.