Draft:Cryptocurrency tracing

Cryptocurrency tracing is a digital forensic technique used to track and analyze the flow of cryptocurrencies across blockchain networks. Law enforcement agencies, regulators, and cybersecurity experts use cryptocurrency tracing to identify and combat crypto fraud.

Cryptocurrencies like Bitcoin and Ethereum use blockchain technology, allowing for "trustless" transactions verified without central intermediaries. Some blockchain networks are transparent and decentralized, providing transaction information specialists can use for tracing purposes. Transparency makes it possible to trace funds across different ledgers, even when criminals try to obscure their origins through techniques like mixing or converting between different cryptocurrencies.

Cryptocurrency tracing techniques include blockchain analysis, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), and cross-ledger transaction tracking. These methods can identify patterns and links between transactions, allowing investigators to establish connections with real-world entities.

In the recent past, cryptocurrency tracing experts worked with law enforcement to bust large-scale frauds, such as advance-fee and phishing scams. Compliance officers can use tracing techniques to enforce anti-money laundering (AML) regulations and secure the integrity of cryptocurrency ecosystems.

Background
Cryptocurrency tracing appeared as a consequence of blockchain technology and digital currencies like Bitcoin and Ethereum. Cryptocurrency scams date back to the early days of Bitcoin. As blockchain technology evolved, so did fraud methods. It took a while to discover that many cryptocurrency transactions are traceable. Advanced tracing techniques can fight crypto crime and facilitate security and compliance in the cryptocurrency ecosystem.

Blockchain technology has redefined online transactions. “Trustless” transactions do not require central intermediaries. Digital cash is semi-transparent, meaning that every transaction leaves a record, but nothing links transactions to identities. Perceived anonymity and borderless online transactions have enabled bad actors to target unsuspecting victims through scams like advance-fee fraud and phishing schemes.

Cryptocurrency tracing is a possible answer to crypto scams. Tracing specialists use methods like blockchain analysis, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), and cross-ledger transaction tracking to identify patterns and establish links between transactions. The objective is to link fraudulent activities to real-world identities and criminal networks.

Techniques and Methods
Blockchain researchers have developed and adopted various techniques to track and analyze the flow of digital currencies across blockchain networks, where possible.

Blockchain Analysis

Blockchain analysis peers into the immutable transaction records in blockchain ledgers. By examining transaction histories and identifying patterns, analysts try to link seemingly unrelated transactions and reveal the flow of funds through different addresses and wallets.

DBSCAN

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) identifies groups of related transactions or addresses by analyzing the density of transaction data points. DBSCAN is an algorithm used in machine learning that can reveal networks of addresses controlled by the same entity, despite obfuscation attempts. By clustering these addresses, investigators can gain a clearer picture of the structure and scale of illicit operations.

Cross-ledger Transaction Tracking

Cross-ledger transaction tracking is a technique used to trace the movement of funds across different cryptocurrency networks. Platforms like ShapeShift allow users to exchange one cryptocurrency for another. Investigators can follow funds moving between different blockchains through such platforms, even when criminals try to obscure their origins through currency conversion.

Graph Analysis

Some cryptocurrency tracing specialists use graphs to represent wallets and transactions. The visual representation of blockchain transactions allows investigators to identify patterns, spot address clusters, and gain other insights.

By combining these techniques, law enforcement, regulators, and cybersecurity experts can detect and combat illicit activities, making cryptocurrency ecosystems safer.

Applications
Cryptocurrency tracing has practical applications in law enforcement, financial regulation, and cybersecurity.

Law Enforcement

Tracing techniques assist law enforcement agencies in tracking and recovering illicit funds. Analyzing blockchain transactions allows investigators to track the movement of money from criminal activities such as ransomware attacks, drug trafficking, and fraud. This helps authorities identify and apprehend the individuals involved in these illegal activities.

Financial Regulation

Cryptocurrency tracing helps financial regulators enforce anti-money laundering (AML) regulations. Regulatory agencies can use tracing techniques to monitor and track suspicious transactions that may indicate money laundering or terrorist financing. By ensuring compliance with AML laws, regulators can prevent the use of cryptocurrencies for illegal purposes and preserve the integrity of the financial system.

Cybersecurity

Cybersecurity experts use cryptocurrency tracing to safeguard digital assets and fight cyber threats. By identifying patterns and links between transactions, cybersecurity professionals can detect and mitigate risks associated with cryptocurrency scams and fraud. Clustering and blockchain analysis techniques can help in uncovering large-scale frauds, such as advance-fee and phishing scams.

Examples of successful cryptocurrency tracing applications include recovering funds from scams and dismantling criminal networks. Tracing helped authorities identify and seize assets from fraudulent schemes. Additionally, tracing techniques exposed organized crime groups using cryptocurrencies to launder money and finance illicit activities.

Notable Cases
Cryptocurrency tracing has been pivotal in uncovering and resolving several significant cases involving scams and illicit activities.

Starscape Capital

A notable example is the Starscape Capital scam. In this case, over 2,000 ETH were exchanged for Monero via the ShapeShift platform, obscuring the trail of the stolen funds. Cryptocurrency tracing allowed investigators to track the flow of money across different ledgers and identify the perpetrators behind the scam.

Silk Road

In October 2013, the FBI arrested Ross Ulbricht, the founder of the infamous Silk Road dark web marketplace. Silk Road used Bitcoin for transactions involving drug trafficking.

The FBI used blockchain analysis to identify Ulbricht and seize approximately 144,000 Bitcoins from his wallets. In 2015, Ulbricht was sentenced to life in prison.

Colonial Pipeline Ransomware Attack

In May 2021, cybercriminal group DarkSide executed a ransomware attack on pipeline operator Colonial Pipeline, getting away with a 75-Bitcoin ransom. The FBI teamed up with other cybersecurity experts and followed the flow of funds through the Bitcoin blockchain, identifying the perpetrators. Authorities recovered 63.7 of the 75 Bitcoins initially paid to the criminals.

Clustering methods and blockchain analysis enabled investigators to track these transactions and link them back to the scam operators, resulting in their identification and apprehension.

Challenges and Limitations
Cryptocurrency mixers constitute a significant challenge for tracing efforts. They blend transactions to mask the origins and destinations of funds. These mixers make it difficult to trace the flow of cryptocurrencies and identify the involved parties.

Privacy concerns also present a considerable challenge. The transparency of blockchain technology is beneficial for tracing purposes, but it also raises issues related to user privacy. Tracking transactions across ledgers can infringe on privacy, leading to ethical and legal problems.

Scammers continue to develop new techniques to evade detection, such as using privacy-focused cryptocurrencies like Monero, or fine-tuning their methods. This ongoing “arms race” requires continuous research and development to stay ahead of illicit activities.

These challenges highlight the need for ongoing innovation and cooperation between law enforcement, regulators, and the cybersecurity community to combat cryptocurrency-related crime more effectively.

Future Directions
Cryptocurrency tracing continues to evolve as industry stakeholders improve their collaborative efforts. New technologies, like better algorithms and machine learning techniques, may contribute to better crypto tracing.

Other potential targets for improvement are the integration of cross-ledger analysis capabilities and enhanced collaboration between regulatory bodies, law enforcement agencies, and private sector entities.

By fostering stronger partnerships and sharing information more effectively, these stakeholders can develop comprehensive strategies to combat cryptocurrency-related crimes. Joint efforts in research, training, and the development of standardized protocols will be crucial in enhancing the overall effectiveness of cryptocurrency tracing initiatives.

Regulatory frameworks that adapt to the rapid changes in the cryptocurrency landscape are essential. These include updating anti-money laundering (AML) regulations and ensuring that cryptocurrency exchanges and other related businesses comply with these standards.