Behavioral Analysis of Bitcoin Users on Illegal Transactions

Samsudeen, Zuha; Perera, Dhanushka; Fernando, Mahendra

doi:10.25046/aj040250

Cited by 12 publications

(9 citation statements)

References 32 publications

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“…For example, crypto-mining frauds involve malware which uses a victim’s computer to mine cryptocurrencies for the offender (Anderson et al, 2019 ; Conley et al, 2015 ). In the case of wallet and exchange service frauds, fraudsters impersonate legitimate versions of such services, only to later steal money from victims (Pryzmont, 2016 ; Samsudeen et al, 2019 ; Vasek, 2017 ; Vasek & Moore, 2015 ). These are, perhaps, the only two types of fraud identified which could be considered strictly crypto-dependent, as opposed to other crimes, such as ransomware, which—while cyber-dependent—are merely facilitated by cryptocurrencies.…”

Section: Discussionmentioning

confidence: 99%

“…In the context of cryptocurrencies, fraudsters accumulate volumes of a low-value currency and then aim to artificially inflate its price by spreading misinformation, typically as a coordinated effort over the internet. When the value of the cryptocurrency increases, they sell everything to make a profit (Barnes, 2018 ; Baum, 2018 ; Chen et al, 2019c ) Market manipulation Market manipulation refers to market participants (including exchanges) and bots attempting to change the price of a cryptocurrency (ur Rehman et al, 2020 ) Exchange scam Scams related to cryptocurrency exchange platforms entail the purposeful closing of a platform leading to financial losses for the cryptocurrency owners (Samsudeen et al, 2019 ). To that end, fraudulent exchange services entice victims through unique payment features or high exchange rates (Vasek, 2017 ; Vasek et al, 2015 ).…”

Section: Appendixmentioning

confidence: 99%

“…From the context of the article in which it appears, this form of fraud was understood to refer to creating fake versions of an official website or app (such as an exchange app, etc.) (Scheau et al, 2020 ) a Giveaway scams* In a giveaway scam, a fraudster promises to give victims a reward for sending him/her a particular amount of cryptocurrency (which is never ultimately delivered) (Xia et al, 2020a ) Fake agencies Scammers pretend to be an existing exchange or government organization to steal cryptocurrency from customers (Samsudeen et al, 2019 ) Donation scams* In a donation scam, a fraudster will pretend to be from a public organisation purporting to raise money (using cryptocurrency) for a worthy cause that does not actually exist (Xia et al, 2020a ) Blackmail scams* Blackmail scams were defined and discussed in the studies in the context of COVID-19. They refer to individuals claiming they will spread coronavirus unless the victim sends them cryptocurrency (Xia et al, 2020a ) Arbitrage scams* Arbitrage refers to investors profiting off price imbalances in the market.…”

Section: Appendixmentioning

confidence: 99%

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Cryptocurrencies and future financial crime

et al. 2022

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Background Cryptocurrency fraud has become a growing global concern, with various governments reporting an increase in the frequency of and losses from cryptocurrency scams. Despite increasing fraudulent activity involving cryptocurrencies, research on the potential of cryptocurrencies for fraud has not been examined in a systematic study. This review examines the current state of knowledge about what kinds of cryptocurrency fraud currently exist, or are expected to exist in the future, and provides comprehensive definitions of the frauds identified. Methods The study involved a scoping review of academic research and grey literature on cryptocurrency fraud and a 1.5-day expert consensus exercise. The review followed the PRISMA-ScR protocol, with eligibility criteria based on language, publication type, relevance to cryptocurrency fraud, and evidence provided. Researchers screened 391 academic records, 106 of which went on to the eligibility phase, and 63 of which were ultimately analysed. We screened 394 grey literature sources, 128 of which passed on to the eligibility phase, and 53 of which were included in our review. The expert consensus exercise was attended by high-profile participants from the private sector, government, and academia. It involved problem planning and analysis activities and discussion about the future of cryptocurrency crime. Results The academic literature identified 29 different types of cryptocurrency fraud; the grey literature discussed 32 types, 14 of which were not identified in the academic literature (i.e., 47 unique types in total). Ponzi schemes and (synonymous) high yield investment programmes were most discussed across all literature. Participants in the expert consensus exercise ranked pump-and-dump schemes and ransomware as the most profitable and feasible threats, though pump-and-dumps were, notably, perceived as the least harmful type of fraud. Conclusions The findings of this scoping review suggest cryptocurrency fraud research is rapidly developing in volume and breadth, though we remain at an early stage of thinking about future problems and scenarios involving cryptocurrencies. The findings of this work emphasise the need for better collaboration across sectors and consensus on definitions surrounding cryptocurrency fraud to address the problems identified.

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Section: Discussionmentioning

confidence: 99%

Section: Appendixmentioning

confidence: 99%

Section: Appendixmentioning

confidence: 99%

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Cryptocurrencies and future financial crime

et al. 2022

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“…After analysis of the critical factors for success in blockchain-based services, Prasad et al (2018) Samsudeen et al (2019) describe how the features of bitcoin, namely anonymity, security and decentralization, also create opportunities for illegal and fraudulent activities with the conclusion stressing the importance of automating the process to detect illegal transactions. Scuderi et al (2019) analyzed one of the most valuable, largest and complex industries, the agri-food sector.…”

Section: Bibliographic Coupling Of Documents: Main Themesmentioning

confidence: 99%

Blockchain security research: theorizing through bibliographic-coupling analysis

Patrício

Ferreira

2020

JAMR

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PurposeThe continuous presence and intensity of the Internet of things (IoT) in our lives and the risk of security breaches in traditional transactional and financial platforms are the major cause of personal and organizational data losses. Blockchain emerges as a promised technology to ensure higher levels of data encryption and security. Thus, this study aims to develop a systematic literature review analyzing the previous literature and to purpose of a framework to better understand the process of blockchain security.Design/methodology/approachThe 75 articles reviewed were obtained through the Scopus database and a bibliographic-coupling analysis was developed to identify the main themes of this research area, via VOSviewer software.FindingsThe results enable the categorization of the existing literature revealing four clusters: 1) feasibility, 2) fintech and cryptocurrency, 3) data trust and share and 4) applicability. Blockchain technology is still in its early stage of development and counting on researchers in security and cryptography to take it further to new highs, to allow its applicability to different areas and in long-term scenarios.Originality/valueThis systematic literature creates a base to reduce the blockchain security literature gap. In addition, it provides a framework that enables the scientific community to access the main subjects discussed and the articulation between concepts. Furthermore, it enhances the state-of-the-art literature on blockchain security and proposes a future research agenda.

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“…WalletExplorer is a web-page where data and information about different known entities detected until today are collected. The dataset is continuously being updated and its information has been used as a starting point for many Bitcoin-related studies, such as [15,32,41]. For our purpose, each entity was downloaded with its origin name and its related detected addresses.…”

Section: Datasetsmentioning

confidence: 99%

Bitcoin and Cybersecurity: Temporal Dissection of Blockchain Data to Unveil Changes in Entity Behavioral Patterns

et al. 2019

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The Bitcoin network not only is vulnerable to cyber-attacks but currently represents the most frequently used cryptocurrency for concealing illicit activities. Typically, Bitcoin activity is monitored by decreasing anonymity of its entities using machine learning-based techniques, which consider the whole blockchain. This entails two issues: first, it increases the complexity of the analysis requiring higher efforts and, second, it may hide network micro-dynamics important for detecting short-term changes in entity behavioral patterns. The aim of this paper is to address both issues by performing a “temporal dissection” of the Bitcoin blockchain, i.e., dividing it into smaller temporal batches to achieve entity classification. The idea is that a machine learning model trained on a certain time-interval (batch) should achieve good classification performance when tested on another batch if entity behavioral patterns are similar. We apply cascading machine learning principles—a type of ensemble learning applying stacking techniques—introducing a “k-fold cross-testing” concept across batches of varying size. Results show that blockchain batch size used for entity classification could be reduced for certain classes (Exchange, Gambling, and eWallet) as classification rates did not vary significantly with batch size; suggesting that behavioral patterns did not change significantly over time. Mixer and Market class detection, however, can be negatively affected. A deeper analysis of Mining Pool behavior showed that models trained on recent data perform better than models trained on older data, suggesting that “typical” Mining Pool behavior may be represented better by recent data. This work provides a first step towards uncovering entity behavioral changes via temporal dissection of blockchain data.

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Behavioral Analysis of Bitcoin Users on Illegal Transactions

Cited by 12 publications

References 32 publications

Cryptocurrencies and future financial crime

Cryptocurrencies and future financial crime

Blockchain security research: theorizing through bibliographic-coupling analysis

Bitcoin and Cybersecurity: Temporal Dissection of Blockchain Data to Unveil Changes in Entity Behavioral Patterns

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