Blockchain Forensics

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What Is Blockchain Forensics?

Blockchain Forensics refers to the process that tracks, analyzes, scrutinizes, and observes the data present in the blockchain. It is a part of digital forensics that deals with tokenomics. The main objective of incorporating this process is to detect any fraudulent activities within the blockchain. 

Blockchain Forensics

It involves a varied range of techniques and tools to perform its function. They can be further used to identify any illegal transactions or fraudsters within the network. Also, it is possible to detect any suspicious activity or behavior among the nodes. 

  • Blockchain forensics delves into the examination and scrutiny of data within the blockchain network. Its primary utility lies in uncovering instances of fraud or illicit activities.
  • The forensic analysis journey comprises several vital stages: data gathering, data analysis, visualization of results, and closure of investigations.
  • Within this domain, practitioners employ a range of techniques, including network analysis, address clustering, transaction graph analysis, machine learning, and the utilization of blockchain explorers.
  • In addition to its investigative role, it also plays a pivotal role in fortifying the integrity of the blockchain ledger and nodes. 

Blockchain Forensics Explained

Blockchain forensics deals with any suspicious or illegal activities happening within the blockchain. It is performed by a team of forensic experts or analysts who try to scan the data present in the blockchain. Also, it helps to monitor crypto transactions and analyze the public ledger for any bugs. In short, it is a method used to perform an in-depth analysis of the entire blockchain. So, if a particular blockchain has a group of crypto whales stealing coins, blockchain forensics tools can detect them easily. 

Following are the steps to conduct forensic analysis on the blockchain:

  • Data gathering: The first step is to gather data related to that blockchain, including the block data, metadata, and other transactions. They form the basic tree structure of the blockchain network. 
  • Data analysis: After gathering the required data, the next step is to observe the data set and search for any flaws. It utilizes different blockchain forensic techniques and methods to examine the data. Once done, forensic analysts can identify patterns that could lead to fraud. 
  • Results visualization: Now, the data analysis performed is presented to investors and shareholders who can better understand the results derived. If the outcome performed includes a malicious actor, it is further presented in the court for legal proceedings. 
  • Investigation closure: The final stage of this investigation is to choose a proper set of actions for the findings. This step will help overcome the fraud happening on the blockchain. 

Techniques

Different techniques and methods are used in the process of performing blockchain forensics. Let us look at them in detail:

#1 - Network Analysis

As the name suggests, the network analysis concentrates on the network utilized by the nodes. It analyzes the IP addresses, geolocation information, and other related data. In short, this analysis tries to peep into the network and scan for any nodes participating in any illegal activity. 

#2 - Clustering Of Addresses

Every transaction performed on the blockchain has a crypto address attached to it. It acts as an identity for the user trading coins. This process of using blockchain addresses is known as address clustering. So, with the help of this technique, it is possible to find any linked addresses or users engaged in malicious attacks. 

#3 - Machine Learning

Machine learning helps forensic analysts to scan giant blockchain data sets and detect any errors. It helps to leverage data, monitor algorithms, and identify such illegal activities. So, if a hacker manipulates the algorithm, machine learning can be helpful to detect them. 

#4 - Blockchain Explorer

Another popular tool used by blockchain forensics companies is Blockchain Explorer. Akin to any other search engine, this explorer helps to find transaction details in seconds. This information includes hash data, block height, and sender or receiver's address. Thus, it is simple and quick to identify any user's details. 

#5 - Transaction Graph Analysis

Every transaction present in the blockchain ledger has a connection with other transactions. If 200 Bitcoins are transferred to Wallet B, some of them might further act as a balance to another wallet. Thus, by creating a graph of these transactions, it is possible to identify patterns of fraudulent activity. 

Examples

Let us look at some hypothetical and real examples to understand the concept more easily.

Example #1

Suppose James owns a company that is purely indulged in blockchain technology. For the past four years, they achieved a remarkable milestone and soon decided to launch their crypto coin AUT. As soon as the coin was launched, the demand and popularity also rose. However, customers were always facing a bug in their trading experience. And it resulted in the loss of some coins. So, James and his team decided to find the root cause of this problem. They consulted forensic experts and conducted a detailed analysis. In no time, the blockchain forensic team found the bug within the network. 

In the result visualization, the forensic experts explained how the network node interrupted the system and was stealing coins. And the result was that James identified the person and filed a lawsuit against him. In addition to it, James also ensured that the company developed a robust security system to refrain any malicious actors from interrupting the system. 

Example #2

According to recent crypto news published in February 2024, blockchain forensic expert A&D Forensics has trained its team to track dubious and suspicious cryptocurrency transactions on the blockchain network. The primary purpose of including this training system was to protect the interests of the customers using the payment gateways. Since financial institutions like banks involve money at regular use, risks of money laundering, theft, and fraud are always present. 

Importance

This concept is a crucial part of blockchain forensics companies and blockchain-based products. They use it frequently to maintain the integrity and authenticity of the blockchain platform. Yet, there is more significance to it. Let us look at the points explained below:

  1. Investigates Fraudulent Activities - The prevalence of blockchain forensics is used mainly in firms to investigate any fraud or financial crimes happening on the network. It helps to identify dark web scams occurring in the crypto wallets. Likewise, firms can also use forensic tools to collect evidence against such activities. 
  2. Secures The Blockchain Network - Since it is possible to identify and detect scammers, the blockchain remains secure and immutable. The network develops a robust security structure to block any malicious actor from disrupting the system. Hence, the occurrence of such crypto attacks reduces to a greater extent. 
  3. Helps In Identifying P2P Scams - Peer-to-peer scams are a frequent activity in the blockchain network. And they can sometimes be challenging to track and detect. However, with the use of blockchain forensics tools, it is feasible to carry out investigation and identify risky addresses and fake assets. 
  4. Adheres to Standards - Lastly, forensic analysis can help companies in adhering to the standards of the business. Thus, they can easily track the flow of funds and assets that are otherwise in the hacker's wallet.

Frequently Asked Questions (FAQs)

1. What are the different blockchain forensics tools present?

The various tools used by analysts in this field are as follows:

a. Elliptic
b. Chainalysis
c. Clinpath
d. Coinfirm
e. Crystal blockchain

2. How is artificial intelligence used in blockchain forensics?

Artificial intelligence (or AI) acts as a robust analytical tool in the identification of forensics. It helps in recognizing different patterns and signal anomalies within the data sets. Also, AI and machine learning models can find any anonymity in the trader's behavior and flag it as a fraudulent activity. In addition to it, these models can also predict future outcomes with the current data and represent it in a graphical format.

3. Which are the popular blockchain forensics case studies?

In the history of blockchain, six major case studies involved blockchain forensics. Let us look at them:

a. In 2013, the Silk Road case involved a dark web case with different Bitcoin coins.
b. Mt. Gox case of 2014.
c. BTC-e Investigation case of 2017.
d. The PlusToken scam included the theft of millions of dollars.
e. Twitter Bitcoin scam of 2020.
f. Colonial Pipeline Ransomware Attack Recovery of 2021.