Blockchain and Fraud Detection | What impact do the characteristics of blockchain technology have on fraud detection in the Bitcoin network

Context

Since the launch of Bitcoin, the world has witnessed intense research and development efforts in blockchain technology. This innovative technology, which acts as a distributed ledger, allows multiple parties to record and verify transactions in a secure and transparent manner. However, there are still significant difficulties regarding the processing and use of cryptocurrencies. The history of Bitcoin, the first cryptocurrency based on blockchain, shows how the properties of this technology can be misused for criminal activities. A striking example of this is the case of Silk Road, a website that operated from 2011 to 2013 and was ultimately shut down by the FBI. This platform enabled the anonymous purchase of a wide range of services and products, including computer hacking services and drugs, which were mainly sold in Europe and North America. Payment was made in Bitcoin; when the platform was shut down, the government confiscated 173,000 Bitcoins from the servers that ran Silk Road. Given the rapid development of this technology, the study of methods to strengthen the integrity and security of the systems is of great importance. While several studies have already been conducted on anomaly and fraud detection using statistical and data mining methods, there is still a lack of research focusing on the framework and handling of these networks. One of the biggest challenges in introducing new technologies is often the fear and scepticism they generate. This is especially true of blockchain technology, which is challenging to control and legislate due to its unique features. One aspect of both the anonymity and another aspect of the technology's global reach are the sources of the issue. This poses a huge challenge for all governments, as an international approach is crucial. The main research question of this thesis is whether the characteristics of blockchain technology have an influence on fraud detection in the Bitcoin network. The main objective of this study is to provide a comprehensive and in-depth overview of the topic of blockchain and, in particular, to explore the impact of its specific characteristics on fraud detection in the Bitcoin network. This research aims to provide insights into how the characteristics of blockchain technology, such as its transparency, decentralization, and security aspects, can hinder the detection of fraudulent activities within the bitcoin network.

Methodology

To gain a comprehensive insight into blockchain technology and anomaly and fraud detection, relevant books, reports, and research were identified using Google Scholar and Chat-GPT. To answer the research question of this thesis, a thorough literature review was conducted, as was the development of a method to detect fraud in the datasets provided by the topic sponsor. Both older and current reports, studies, and books were consulted as part of the knowledge building and information research. After completing the literature research, the code was created with Python in a Jupyter notebook. The datasets used were from 2009 and 2010 and included both incoming and outgoing transactions on the Bitcoin network. Finally, the findings from the literature research were compared with the results of the developed method in order to formulate a conclusion for the work.

Structure

The first section of the thesis explains relevant fundamentals in the field of data science. These are particularly important for the development of methods for the detection of anomalies and fraud. The following section deals with the analysis of the characteristics of blockchain technology, cryptocurrencies, and possible anomalies and fraud. It takes a look at the development of blockchain technology and presents the most important cryptocurrencies and the concept of smart contracts. The rest of the paper examines the regulatory issues and tax aspects of cryptocurrencies and blockchain technologies. A focus will be placed on the challenges and key advantages of this technological innovation. Then, methods that are currently in use for fraud and anomaly detection are given. There are also explanations of approach combinations that have been used successfully in practise. The last part of the work is dedicated to a case study. Here, a code is created to identify unusual transactions in transaction records from the Bitcoin network and to determine the owner. The aim is to gain a better understanding of how fraud detection works and what it can do in blockchain-based systems.

Results

The literature research carried out made it clear that blockchain technology has developed rapidly in the past. Numerous concepts, such as smart contracts, can bring significant benefits in a wide range of areas. The special characteristics of blockchain technology in terms of security, traceability, and decentralisation are proving to be very useful for a wide range of application areas.
Based on the developed use case and the findings from the theory, the research question can be answered as follows: The characteristics of blockchain technology have an impact on fraud detection in the Bitcoin network. As the use case showed, potential fraudulent transactions and wallets could be found in data sets from 2009 and 2010 using a simple statistical method and compared with a database. The properties of anonymity and pseudonymity have no influence on fraud detection but on the prosecution of criminals. However, the traceability and publicity properties have a positive impact on fraud detection. Since all transactions are stored to ensure traceability and the transaction and wallet data are publicly available, transactions made more than 13 years ago could be analysed without the permission of a third party.