According to previous research, cryptocurrency is a driver of money laundering and is associated with several risks (Fletcher, Larkin, & Corbet, 2021; Teichmann & Falker, 2020; Tsuchiya & Hiramoto, 2021). As a result, the purpose of this paper is to concentrate on empirical research in the accounting and finance fields that deal with the impact of cryptocurrencies on the phenomenon of money laundering. To identify relevant literature, we use the following keywords including âcryptocurrency or digital moneyâ and âbitcoin and money launderingâ. We identify 28 research papers published between 2011 and 2021. The findings of the studies that were reviewed emphasized the importance of developing a legal framework for digital currencies. Furthermore, it was revealed that all stakeholders play an important role in lowering the risk of money laundering and illicit activities. The findings highlight the critical role that banks, regulators, and all stakeholders play in reducing money laundering risks. These findings may have policy implications for governments aiming to improve cryptocurrency laws and regulations by enforcing financial security standards and laws and monitoring individualsâ and firmsâ compliance with them. The review identifies some of the literatureâs limitations and suggests future research directions
Nowadays, health insurance has become an essential part of people’s lives as the number of health issues increases. Healthcare emergencies can be troublesome for people who can’t afford huge expenses. Health insurance helps people cover healthcare services expenses in case of a medical emergency and provides financial backup against indebtedness risk. Health insurance and its several benefits can face many security, privacy, and fraud issues. For the past few years, fraud has been a sensitive issue in the health insurance domain as it incurs high losses for individuals, private firms, and governments. So, it is essential for national authorities and private firms to develop systems to detect fraudulent cases and payments. A high volume of health insurance data in electronic form is generated, which is highly sensitive and attracts malicious users. Motivated by these facts, we present a systematic survey for Artificial Intelligence (AI) and blockchain-enabled secure health insurance fraud detection in this paper. This paper presents a taxonomy of various security issues in health insurance. We proposed a blockchain and AI-based secure and intelligent system to detect health insurance fraud. Then a case study related to health insurance fraud is presented. Finally, the open issues and research challenges in implementing the blockchain and an AI-empowered health insurance fraud detection system is presented.
In recent years, the application of virtual currency has become a part of people's life. The decentralization and anonymity of Bitcoin have made it a favorite tool for many criminals. Therefore, how to trace illegal activities in Bitcoin transactions has become one of the most important research areas. This paper systematically collects 25 research results in this field since 2018, and divides them into three areas, i.e., supervised learning, unsupervised learning, and topological analysis. The supervised learning method based on machine learning is the current mainstream in this research field. However, we believe that the model can achieve more accurate results after combining unsupervised learning and topological analysis features. Moreover, topology analysis can help to observe the entire or specific part of the Bitcoin trading network from a macro perspective so as to discover the hidden illegal activities. In addition, data visualization techniques can provide structural insights to understand the Bitcoin trading network.
Blockchain technology supports the generation and record of transactions, and maintains the fairness and openness of the cryptocurrency system. However, many fraudsters utilize smart contracts to create fraudulent Ponzi schemes for profiting on Ethereum, which seriously affects financial security. Most existing Ponzi scheme detection techniques suffer from two major restricted problems: the lack of motivation for temporal early warning and failure to fuse multi-source information finally cause the lagging and unsatisfactory performance of Ethereum Ponzi scheme detection. In this paper, we propose a dual-channel early warning framework for Ethereum Ponzi schemes, named Ponzi-Warning, which performs feature extraction and fusion on both code and transaction levels. Moreover, we represent a temporal evolution augmentation strategy for generating transaction graph sequences, which can effectively increase the data scale and introduce temporal information. Comprehensive experiments on our Ponzi scheme datasets demonstrate the effectiveness and timeliness of our framework for detecting the Ponzi contract accounts.
PURPOSE: The main purpose of this paper was to identify the current scope of research on cryptocurrencies as a subject of fraud. Detailed research questions related to the determination of contemporary trends of the conducted research and the definition of potential opportunities for further investigation of this topic. One of the questions also concerned identifying the most common crimes committed using cryptocurrencies. METHODOLOGY: The study is based on a systematic literature review (SLR) of 57 publications available on the Scopus database. A bibliometric and descriptive analysis of selected literature items was carried out. Then, vital thematic clusters were separated, and an in-depth content analysis was performed. FINDINGS: The detailed bibliometric and descriptive analysis showed that cryptocurrencies as a subject of financial fraud are generally a new area of scientific research, although it is developing quite intensively. The relatively small number of publications, compared to other similar areas, also indicates that this topic has not yet been explored widely by scientists, and many different research trends can be created in it. Ultimately, the following key research areas were identified: types of cryptocurrency fraud, crime detection methods, risks related to blockchain technology, money laundering, and legal regulations regarding cryptocurrencies. It was also possible to identify that money laundering is currently the most common fraud. However, it has been pointed out that the second most frequent fraud is financial pyramids based on the Ponzi scheme. IMPLICATIONS: The paper clearly presents the main research trends on using cryptocurrencies in criminal activities. At the same time, it was emphasized that, compared to other research areas, this topic is relatively new. Therefore, there is a wide possibility of exploring not only existing but also undiscovered research trends. In addition, key types of fraud in economic practice have been identified, which is particularly important for financial market participants. It was clearly indicated which transactions bear the highest risk. It is also worth paying attention to the critical timeliness of the topic, as the scale of crimes involving cryptocurrencies has recently been growing rapidly. The study confirms the insufficient scope of legal regulations, which are not able to strengthen the security of economic transactions adequately. Therefore, it can be a clear indication for the governments of individual countries or international institutions for further efficient changes to the law. ORIGINALITY AND VALUE: The contribution of this study is threefold. It is one of the first research papers showing the results of a systematic literature review (SLR) combined with a bibliographic and in-depth analysis of the content of publications in this field. During the work, the VOSviewer software was also used, which enabled objective identification of the main thematic clusters based on the occurrences and link strength of keywords included in the publications. Secondly, the key types of fraud have been identified that, at the same time, cause the most significant financial loss. This allowed for the establishing of directions for further research, which have profound practical implications for market participants. Some of them relate to the need to develop and implement modern computer applications, allowing for the detection of a wider range of emerging abuses.
Jie Cai, Bin Li, Jiale Zhang, Xiaobing Sun · 5 authors
Smart contract security has drawn extensive attention in recent years because of the enormous economic losses caused by vulnerabilities. Even worse, fixing bugs in a deployed smart contract is difficult, so developers must detect security vulnerabilities in a smart contract before deployment. Existing smart contract vulnerability detection efforts heavily rely on fixed rules defined by experts, which are inefficient and inflexible.To overcome the limitations of existing vulnerability detection approaches, we propose a GNN based approach for smart contract vulnerability detection. First, we construct a graph representation for a smart contract function with syntactic and semantic features by combining abstract syntax tree (AST), control flow graph (CFG), and program dependency graph (PDG). To further strengthen the presentation ability of our approach, we perform program slicing to normalize the graph and eliminate the redundant information unrelated to vulnerabilities. Then, we use a Bidirectional Gated Graph Neural-Network model with hybrid attention pooling to identify potential vulnerabilities in smart contract functions.
Kai Wang, Jun Pang, Ding-Jie Chen, Yu Zhao · 7 authors
Exploiting the anonymous mechanism of Bitcoin, ransomware activities demanding ransom in bitcoins have become rampant in recent years. Several existing studies quantify the impact of ransomware activities, mostly focusing on the amount of ransom. However, victimsâ reactions in Bitcoin that can well reflect the impact of ransomware activities are somehow largely neglected. Besides, existing studies track ransom transfers at the Bitcoin address level, making it difficult for them to uncover the patterns of ransom transfers from a macro perspective beyond Bitcoin addresses. In this article, we conduct a large-scale analysis of ransom payments, ransom transfers, and victim migrations in Bitcoin from 2012 to 2021. First, we develop a fine-grained address clustering method to cluster Bitcoin addresses into users, which enables us to identify more addresses controlled by ransomware criminals. Second, motivated by the fact that Bitcoin activities and their participants already formed stable industries, such as Darknet and Miner , we train a multi-label classification model to identify the industry identifiers of users. Third, we identify ransom payment transactions and then quantify the amount of ransom and the number of victims in 63 ransomware activities. Finally, after we analyze the trajectories of ransom transferred across different industries and track victimsâ migrations across industries, we find out that to obscure the purposes of their transfer trajectories, most ransomware criminals (e.g., operators of Locky and Wannacry) prefer to spread ransom into multiple industries instead of utilizing the services of Bitcoin mixers. Compared with other industries, Investment is highly resilient to ransomware activities in the sense that the number of users in Investment remains relatively stable. Moreover, we also observe that a few victims become active in the Darknet after paying ransom. Our findings in this work can help authorities deeply understand ransomware activities in Bitcoin. While our study focuses on ransomware, our methods are potentially applicable to other cybercriminal activities that have similarly adopted bitcoins as their payments.
Targets of cyber crime are not exclusive to the private sector. Successful cyber attacks on nation-states have proved that cyber threats can jeopardize significant national interests. In response, nation-states have begun to handle cyber threats at the national defense level, which is titled ‘cyber defense.’ The cyber defense sector is related to national security, therefore requires robust security technology. Contrary to normal systems, blockchain provides strong security properties without a centralized control entity, and as such its application in the cyber defense field is under the spotlight. In this paper, we present opportunities blockchain provides for cyber defense, research and national projects, and limitations. We constructed a survey of government documents, interviews, related news, technical reports, and research papers from 2016 to 2021. As a result, our research contributes to reducing the gap in blockchain for cyber defense by systematically conducting research and analysis. In our research, we found that not only research but also government-led plans are actively promoting blockchain, which demonstrates that blockchain will play a remarkable role in cyber defense. This paper concludes with suggestions for future research in aspects of the blockchain technology, evaluation, and survey.
Bitcoin's attack in finance has caused a new wind to blow in the stock market and with the emergence of many new crypto currencies, the crypto currency market has become a new financial area. Although Blockchain technology is the technological infrastructure of Bitcoin, awareness is not as high as Bitcoin. Despite it was found in 1992, its first use was in the shadow of Bitcoin, influenced by the fact that it was with Bitcoin in 2008. However, due to the features that it provides; Without Blockchain technology, the Bitcoin system would not work. As the dazzling offer of Bitcoin; through the decentralized structure, buyers and sellers can meet directly on a platform and make their purchases securely, without involvement of any third party. Verification in the system can only be done by approving by more than 50% of the participants. Thus, besides of no need for a central authority, it became almost impossible for any cyber attack to be successful. The continued success of Blockchain technology is vital for Bitcoin and other cryptographic currencies survival. Beside of all these advantages, there are some issues that need to be addressed for Blockchain technology. These can be listed as throughput, latency in processing, size and bandwidth, some security vulnerabilities, resource waste for adding a new block to chains, usability, and privacy. In this article, we will discuss these issues that need to be addressed for Blockchain technology.
Abstract Decentralized Finance (DeFi) is a system of financial products and services built and delivered through smart contracts on various blockchains. In recent years, DeFi has gained popularity and market capitalization. However, it has also been connected to crime, particularly various types of securities violations. The lack of Know Your Customer requirements in DeFi poses challenges for governments trying to mitigate potential offenses. This study aims to determine whether this problem is suited to a machine learning approach, namely, whether we can identify DeFi projects potentially engaging in securities violations based on their tokensâ smart contract code. We adapted prior works on detecting specific types of securities violations across Ethereum by building classifiers based on features extracted from DeFi projectsâ tokensâ smart contract code (specifically, opcode-based features). Our final model was a random forest model that achieved an 80% F-1 score against a baseline of 50%. Notably, we further explored the code-based features that are the most important to our modelâs performance in more detail by analyzing tokensâ Solidity code and conducting cosine similarity analyses. We found that one element of the code that our opcode-based features can capture is the implementation of the SafeMath library, although this does not account for the entirety of our features. Another contribution of our study is a new dataset, comprising (a) a verified ground truth dataset for tokens involved in securities violations and (b) a set of legitimate tokens from a reputable DeFi aggregator. This paper further discusses the potential use of a model like ours by prosecutors in enforcement efforts and connects it to a wider legal context.
Marina Liu, William Yeoh, Frank Jiang, KimâKwang Raymond Choo
Blockchain has transitioned beyond the hype to reality, as evidenced by the amount of research it has attracted and by its commercial applications. One popular application of blockchain is in cybersecurity, which is the focus of this paper. Specifically, we performed a systematic literature review of blockchain use cases for cybersecurity, while focusing on articles published over the past decade. Based on our analysis of 111 articles, we developed a classification framework using the thematic analysis approach. This classification framework is designed to offer readers a comprehensive perspective of the potential of blockchain to enhance cybersecurity in different contexts. The findings have implications for research and practice.
Abstract The pronounced multi-domain technologicalization specific to the last decades has had a significant impact on all areas of activity, including the financial one. The use of cyberspace to facilitate the actions undertaken in the monetary activity has generated the development of this field to the point where virtual currencies have been created and new technologies have been developed to support their use. Like any emerging domain, the cryptocurrency field and the related technology are in a relatively early stage and exclusively imply operating in cyberspace, thus generating security risks in the event of the involvement of malicious entities in illicit activities. In this context, it is worth analyzing how the improper use of the crypto domain can lead to various risks to national security.
Recently, phishing scams have posed a significant threat to blockchains. Phishing detectors direct their efforts in hunting phishing addresses. Most of the detectors extract target addressesâ transaction behavior features by random walking or constructing static subgraphs. The random walking methods, unfortunately, usually miss structural information due to limited sampling sequence length, while the static subgraph methods tend to ignore temporal features lying in the evolving transaction behaviors. More importantly, their performance undergoes severe degradation when the malicious users intentionally hide phishing behaviors. To address these challenges, we propose TEGDetector, a dynamic graph classifier that learns the evolving behavior features from transaction evolution graphs (TEGs). First, we cast the transaction series into multiple time slices, capturing the target addressâs transaction behaviors in different periods. Then, we provide a fast nonparametric phishing detector (FD) to narrow down the search space of suspicious addresses. Finally, TEGDetector considers both the spatial and temporal evolutions toward a complete characterization of the evolving transaction behaviors. Moreover, TEGDetector utilizes adaptively learned time coefficient to pay distinct attention to different periods, which provides several novel insights. Extensive experiments on the large-scale Ethereum transaction dataset demonstrate that the proposed method achieves state-of-the-art (SOTA) detection performance. The code of TEGDetector is open sourced at https://github.com/Seaocn/TEGDetector.
JT Hamrick, Farhang Rouhi, Arghya Mukherjee, Marie Vasek · 6 authors
As the number of cryptocurrencies has exploded in recent years, so too has the fraud. One popular strategy is when actors promote coordinated purchases of coins in hopes of temporarily driving up prices. Prior work investigating such pump and dump schemes has focused on the immediate impact to prices following pump signals, which were largely interpreted as following the same strategy. The reality, as with most cybercrimes, is that the operators of the schemes try out a much more heterogeneous mix of tactics. From a population of 12,252 pump signals observed between July 2017 and January 2019, we identify and examine 3,683 so-called target-based pump signals that announce promoted coins alongside buy and sell targets, but without a coordinated purchase time. We develop a strategy to measure the success of target pumps over longer time horizons. We find that around half of these pumps reach at least one of their sell targets, and that reaching their peak price often takes days, as opposed to the seconds or minutes required in pumps studied previously. We also examine the various groups promoting coins and present evidence that groups try a variety of distinct strategies and experience varying success. We find that the most successful groups promote many coins and issue many pumps, but not for the same coins. As decentralized finance becomes more popular, a deeper understanding of price manipulation techniques like target pumps is needed to combat fraud.
Crime research has repeatedly shown that small proportions of offenders are responsible for large proportions of crimes. While there is a substantial body of evidence for this âoffending concentrationâ in connection to traditional offline crime, there is limited research assessing the concentration of offending for cybercrime. This research analyzes victim reports of Bitcoin-related cybercrimes (blackmail, ransomware, sextortion, darknet market fraud, Bitcoin tumbler fraud) to illuminate the extent of cybercrime offending concentration and to identify groups of offenders involved in online crime. Our results indicate that a large proportion of cybercrimes are associated with a small number of very active Bitcoin addresses. However, Bitcoin addresses associated to high numbers of reports are not necessarily those that generate the largest financial benefits.
Abstract The rise of cryptocurrencies during the last decade has caused growing concerns among national and international regulators. One of the risks identified is that these instruments may constitute an innovative tool for criminals when laundering money. This risk has been confirmed by numerous recent cases which have underlined the criminogenic potential of cryptocurrencies. Through the V antimoney laundering (AML) Directive, the European legislator has first regulated this emerging issue. This legislation extends the AML duties to two players of the cryptocurrencies market: exchangers and wallet providers. This choice, however, does not exploit the opportunities offered by cryptocurrencies and fails to provide a customized regulatory framework. By maintaining a traditional regulatory approach centered on intermediaries it misses the key innovation of blockchain technology: disintermediation. Compared with traditional online money flows, intermediaries are not necessary nor fundamental in the cryptocurrencies environment. Failing to adapt to this reality, the Directive is employing chivalry to fight a trench war. To guarantee the integrity of this market, the policymaker has to abandon the traditional intermediaryâcentred approach in favor of a strategy that seizes the new opportunities offered by blockchain. This paper advocates for a shift from an individualâcentered approach to financial crime control to a transactionâcentered one.
The increasing popularity of cryptocurrencies has raised many questions with regard to their regulation. Issues such as taxation and its role in criminal activities are of central importance to the way in which cryptocurrency will continue to develop and occupy space in society. In this paper, such regulatory aspects are explored, and South Africaâs response is addressed. With cryptocurrency growing worldwide at increasing rates, regulators are left having to respond quickly to this aspect of financial technology and while some have banned its use outright, others have taken the stance to embrace the use of cryptocurrencies to ensure it has a space for use in the future of the financial world.
On January 26, 2018, 58 billion yen ($530 million) worth of a cryptocurrency, NEM, was fraudulently accessed, and was then stolen from the Coincheck Exchange, headquartered in Japan. This hacking incident is unprecedented not only because it was one of the worldâs largest cryptocurrency heists, but also because the stolen NEM was sold and money laundered on a crypto market. Three years later, the Metropolitan Police Department, Japan, announced that more than 30 people had been charged for allegedly exchanging NEM cryptocurrency, accounting for one third of the stolen value, for other cryptocurrencies. The hackers have not yet been arrested, and how the stolen NEM was money laundered has not yet been investigated. By resolving two challenges in tracking the stolen NEM and its money laundering, this report shows that there were increasingly larger sales of the stolen NEM over time, and on the last two days of market operation, approximately one third of the stolen NEM was money laundered. Furthermore, this study reveals that there was no pattern in the hour of the day of the sales transactions whereas more sales occurred on Sundays and Mondays. This suggests that the laundering was international and that the stolen NEM was purchased by individuals. These findings emphasize the need for cryptocurrency exchanges to verify the identity of a new user when an account is opened.
Bitcoin, a decentralized cryptocurrency, has not only given rise to a wave of digital innovations but also stirred up considerable controversy. Some have hailed it as the most significant innovation since the Internet, while others have dismissed it as a Ponzi scheme that should be abandoned and forbidden. Regardless of these varying views, this is an innovation in need of scrutiny. In this paper we present a metastory of Bitcoin, based on an interpretative study of 737 news articles between 2011â2019. Through our analysis, we identified five narratives, including The Dark Side, The Bright Side, The Tulip Mania, The Idea, and The Normality. Our analysis demonstrates the interpretive flexibility of technology as influenced by ideologies, and we construct a theoretical model demonstrating mediaâs role as constructor and conduit. The metastory provides an institutional look at the broader interpretations of digital innovations as well as the multifaceted nature of digital innovations and how their interpretation evolve over time.
In this article, the author primarily aims to clarify from a technical and terminological point of view several notions relevant for the blockchain ecosystem. In this context, the analysis is focused on notions such as blockchain, Proof of Work or Proof of Stake consensus mechanism, virtual currency, crypto-asset, digital wallet, centralized or decentralized exchange platform, public address, public and private cryptographic key, seed phrase, etc. Beyond these technical and terminological clarifications, the author aims to analyse the European and national regulatory framework, in an attempt to resolve, among other things, different matters such as the difference between virtual currencies, crypto-assets and electronic money or the regulation of exchange service providers and digital wallet providers. Last but not least, the author analyses both the risks and benefits of blockchain technology from a cyber security perspective, as well as several criminal behaviours in regard to virtual currencies or other crypto-assets. In this context, behaviours such as ransomware, cryptojacking, unauthorized transfer of virtual currencies or other cryptocurrencies, counterfeiting of virtual currencies, cloning or restricting access to digital wallets, etc. are all taken into consideration.
Cryptocurrencies are a subset of virtual currencies that have been devised for anonymous payments made entirely independent of governments and traditional financial institutions. The payment system of cryptocurrencies is expanding at a rapid pace and has reached Ethiopia. This article examines the extent to which cryptocurrencies are regulated under Ethiopiaâs national payment system and anti-money laundering legal norms. The study has employed doctrinal research supported by in-depth interviews. During the last decade, Ethiopia has adopted several legal frameworks that govern different aspects of the payments landscape, most notably regarding payment services and electronic money. The country has anti-money laundering legal norms that are embodied in domestic laws and international and regional instruments that it has ratified. However, these legal norms have strategic deficiencies in regulating cryptocurrencies. Thus, the government of Ethiopia should consider enacting a comprehensive law that regulates the payment system of cryptocurrencies.
The prosperity of the cryptocurrency ecosystem drives the need for digital asset trading platforms. Beyond centralized exchanges (CEXs), decentralized exchanges (DEXs) are introduced to allow users to trade cryptocurrency without transferring the custody of their digital assets to the middlemen, thus eliminating the security and privacy issues of traditional CEX. Uniswap, as the most prominent cryptocurrency DEX, is continuing to attract scammers, with fraudulent cryptocurrencies flooding in the ecosystem. In this paper, we take the first step to detect and characterize scam tokens on Uniswap. We first collect all the transactions related to Uniswap V2 exchange and investigate the landscape of cryptocurrency trading on Uniswap from different perspectives. Then, we propose an accurate approach for flagging scam tokens on Uniswap based on a guilt-by-association heuristic and a machine-learning powered technique. We have identified over 10K scam tokens listed on Uniswap, which suggests that roughly 50% of the tokens listed on Uniswap are scam tokens. All the scam tokens and liquidity pools are created specialized for the "rug pull" scams, and some scam tokens have embedded tricks and backdoors in the smart contracts. We further observe that thousands of collusion addresses help carry out the scams in league with the scam token/pool creators. The scammers have gained a profit of at least \$16 million from 39,762 potential victims. Our observations in this paper suggest the urgency to identify and stop scams in the decentralized finance ecosystem, and our approach can act as a whistleblower that identifies scam tokens at their early stages.
Simona Ramos, Fabio Pianese, Thomas Leach, Ester Oliveras
A non-traditional type of financial asset, cryptocurrencies based on public blockchains are still little understood in their real-world behavior. Exogenous events such as cyber-attacks and their media coverage can strongly affect their supply and demand, adoption and usage, efficiency, and infrastructural development, thus influencing their price stability and market valuation. Given the great technical complexity of blockchains, we believe that a pure economic analysis of risks associated with cryptocurrencies is simply not sufficient to convey the relationships between attacks and the disruptive effects that these can bring on the operation of cryptocurrencies. On these grounds, we survey the most common types of attacks for Proof-of-Work (PoW) cryptocurrencies and evaluate their impact on the returns of a number of real-world cryptocurrencies for which market data are available. Due to data availability, our event study analysis focuses on instances of 51% attacks, hard forks, and wallet attacks. The main goal of our analysis is to understand the relationship between technical events (cyber-attacks and coordinated user/miner behavior) and the economic impacts surrounding them. We aim to develop a deeper understanding of these systems that are objects of great research interest in separate disciplines, supporting policymakers in their regulatory decisions concerning crypto-assets and associated cyber-related financial risks.