Blockchain Papers

Louis Bertucci

No abstract is available for this record.

Hugo Almeida, Pedro Pinto, Ana Fernández Vilas

Cryptocurrencies are considered relevant assets and they are currently used as an investment or to carry out transactions. However, specific characteristics commonly associated with the cryptocurrencies such as irreversibility, immutability, decentralized architecture, absence of control authority, mobility, and pseudo-anonymity make them appealing for money laundering activities. Thus, the collection and characterization of current cryptocurrency-based methods used for money laundering are paramount to understanding the circulation flows of physical and digital money and preventing this illegal activity. In this paper, a collection of cryptocurrency transaction methods is presented and distributed through the money laundering life cycle. Each method is analyzed and classified according to the phase of money laundering it corresponds to. The result of this article may in the future help design efficient strategies to prevent illegal money laundering activities.

Muhammed Zakir Hossain

No abstract is available for this record.

Imtiaz Sifat, Denise van Donselaar, Syed Ahzam Tariq

No abstract is available for this record.

Jinsha Zhao, Jia Miao

Using Russian-Ukraine war as an exogenous event, we investigate whether Bitcoin is used to evade financial sanctions. We follow three avenues to explore this problem. First, we investigate Bitcoin trading volume pre- and post- Russia's invasion. Second, we explored price and return relationships between Bitcoin and other major asset classes during the same period. Lastly, we investigate the associations between Bitcoin trading volume and Russia oil export by sea. Overall, our results suggest that Bitcoin is not used to evade sanctions in large scale.

Andrea Podhorsky

This paper develops a theoretical model of the bitcoin market and demonstrates that the bitcoin’s volatile and explosive price path is a consequence of the Bitcoin protocol’s system of supply management. The model implies that the marginal cost of mining the target supply of bitcoins is the fundamental value of the bitcoin since it corresponds to an equilibrium in the Bitcoin protocol and the rent-seeking tournament among miners. The data provide strong empirical evidence of cointegration between the bitcoin’s price and the marginal cost of mining the target supply of bitcoins, demonstrating the existence of their long-run equilibrium relationship. Current bubble detection techniques indicate that there is no evidence of explosive departures in the price of the bitcoin from its model-implied fundamental value. Since the raw price data exhibit explosive behavior, the apparent bubbles in the price of the bitcoin can be attributed to its nonstationary market fundamentals. • The bitcoin’s price dynamics result from the protocol’s interference in the market. • The Bitcoin protocol works against the self-correcting mechanism of the market. • Adjustments of the difficulty result in volatile and explosive behavior in the price. • There is cointegration between the bitcoin’s price and the marginal cost of mining. • Apparent bubbles in the price can be attributed to nonstationary market fundamentals.

Lin William Cong, Kimberly Grauer, Daniel Rabetti, Henry Updegrave

We provide an overview of crypto-related scams, including investment scams, Ponzi schemes, and more recently, rug pulls that are commonly seen in Decentralized Finance (DeFi) projects. We then discuss data sources for studying Initial Coin Offering (ICO) scams, before examining the case of PlusToken, the largest crypto scam, AnubisDAO, the prototypical rug pull, and Luno's anti-scam initiative, a good prototype for other cryptocurrency exchanges and service entities to follow. User protection and education are crucial in preventing scams, despite the fact that they may require efforts from centralized entities and regulators.

Lars Hornuf, Paul P. Momtaz, Rachel J. Nam, Ye Yuan

We examine how cybercrime impacts victims’ risk-taking and returns. Our difference-indifferences analysis of a sample of victims and matched non-victims is in line with prospect theory and suggests that victims increase their long-term total risk-taking after losing part of their wealth. Victims also earn lower risk-adjusted returns in the post-cybercrime period. Victims’ long-term total risk-taking increases because they increase diversifiable risk in the long term. The increased diversifiable risk correlates with victims’ withdrawal from altcoins after cybercrime. At the same time, the reduction in risk-adjusted returns correlates with increased trading activity and churn, due plausibly to managing cybercrime exposure. In the cross-section of Ethereum addresses, we show that the most affluent victims take a systematic approach to restore their pre-cybercrime wealth level, while the least affluent victims turn into gamblers. Finally, a parsimonious forensic model explains a good part of the addresses’ probability of being involved in cybercrime, on both the victim and the cybercriminal side.

Mohammad Khalid Khawrin, Nooman Zadran, Ahmad Helal

The world is on the brink of rewriting business and monitoring history. It is very crucial to mention academically how Afghan crypto-monitory transactions are taking place. even though it is a soft threat to official government organizations via tax evasion, money laundering, and terrorism financing. The qualitative method with content analysis was applied because the data was in textual form. The data was analyzed through Atlis.ti 9. First of all, the interviews were coded, and then themes were created. The result showed that Bitcoin and Binance had the most users, and there were six types of cryptocurrencies in Afghanistan. Furthermore, the advantages and disadvantages were highlighted. Lastly, it was highly suggested that the Afghan government have specific laws for general protection and to gain the benefits of the new world of high technology.

Ruolei Zhang

With the volatile price of Bitcoin having received widespread media and investor attention in recent years, this paper surveys the existing literature on Bitcoin which focuses on the differences between Bitcoin and traditional currencies and the impact on the real economy. In doing so, various literature and scholarly insights are discussed to formally clarify the economic implications of Bitcoin in the absence of a centralised entity. A SWOT approach is then used to analyse its strengths, weaknesses, opportunities and risks, before parsing Bitcoin's price trends and making predictions for the future based on specific events and news. Society remains sceptical and uninformed about this cryptocurrency. The evidence suggests that bitcoin returns are significantly slightly inefficient at this stage, but there is also a great deal of uncertainty about the future and it could be on the move.

Firuze Simay Sezgin, Caner Özdurak

This study investigates the impact of terrorist attacks on the price fluctuations of Bitcoin prices and NFT sales. Although the value proposition of cryptocurrencies, Decentralized Finance, and the whole blockchain revolution is a quicker, cheaper, and more transparent kind of finance, various terrorist organizations tend to use cryptocurrency anonymously to finance their terrorist activities around the world by bypassing the banking system of the regulated countries. The analyses reveal that returns of Bitcoin and NFT markets are positively associated with the organization and funding phases of the terrorist attacks but negatively associated with the post-terrorist attack circumstances, meaning that it generates positive abnormal returns (AR) prior to the attack but creates negative AR right after the attack. Furthermore, while the Bitcoin news impact curve (NIC) is nearly symmetric, the NFT NIC is asymmetric, with positive shocks having significantly more impact on future volatility than negative shocks of the same magnitude. Since previous studies claim that terrorist attack news is good news for Bitcoin returns, we will enrich our AR analysis results with NICs results.

Daniela Penela

Bitcoin is a virtual currency that provides a completely decentralized secure alternative to the currencies currently used. Nakamoto, the creator of this cryptocurrency, published an article on an encryption mailing list in 2008 with the title “Bitcoin: A Peer-to-Peer Electronic Cash System”, thus giving the creation of this virtual currency. This study aims to analyze the Bitcoin and what factors can influence its price, in the context of a pandemic. This work will focus on the bitcoin price and on five different factors likely to have an influence on his price, such as: Hash Rate, Mining Difficulty, Volatility Index, Google Search and Transaction Cost. The period for this research ranges from 15/03/2020 to 14/11/2021, a total of 96 weeks, to integrate the covid-19 factor into the study. The results show that the variables fsCoinCirculation and fsTransationCost are both necessary conditions for an increase on the bitcoin price, but for low values of bitcoin price there are no necessary conditions. Additionally, findings suggest that Hash Rate influences the price of bitcoin. Finally, fsVix variable was found to be a variable with an important implication in price, namely, in its volatility.

Ayuba Napari, İnci Parlaktuna

Owing to the high penetration of cryptocurrencies in the Turkish Economy, we sought to determine whether cryptocurrencies as represented by Bitcoin has become a global risk for the Turkish Lira. To accomplish this, we model the Turkish Lira exchange rate returns volatility using threshold GARCH-M with Bitcoin as an exogenous covariate. Bitcoin was found to be a contributor to Turkish forex volatility up until January 2018 when the ‘ongoing’ currency crisis started. Bitcoin, however, lost its volatility contributory power from January 2018. This result is robust to the inclusion of CBOE-VIX, iShares MSCI Turkey EFT, and the dollar-lira interest rate differential as control variables.

Majd Soud, Ilham Qasse, Grischa Liebel, Mohammad Hamdaqa

Due to the risks associated with vulnerabilities in smart contracts, their security has gained significant attention in recent years. However, there is a lack of open datasets on smart contract vulnerabilities and their fixes that allows for data-driven research. Towards this end, we propose an automated framework for mining and classifying Ethereum’s smart contract vulnerabilities and their corresponding fixes from GitHub and from the Common Vulnerabilities and Exposures (CVE) records in the National Vulnerability Database. We implemented the proposed method in a fully automated framework, which we call AutoMESC. AutoMESC uses seven of the most well-known smart contract security tools to classify and label the collected vulnerabilities based on vulnerability types. Furthermore, it collects metadata that can be used in data-intensive smart contract security research (e.g., vulnerability detection, vulnerability classification, severity prediction, and automated repair). We used AutoMESC to construct a sample dataset and made it publicly available. Currently, the dataset contains 6.7K smart contract vulnerability-fix pairs written in Solidity. We assess the quality of the constructed dataset in terms of accuracy, provenance, and relevance, and compare it with existing datasets. AutoMESC is designed to collect data continuously and keep the corresponding dataset up-to-date with newly discovered smart contract vulnerabilities and their fixes from GitHub and CVE records.

Alex McCord, Philip Birch, Alan Davison

Bei der illegalen Nutzung von Kryptowährungen liefern sich Straftäter:innen, die versuchen, neue Technologie auszunutzen, Ermittler:innen, die versuchen, Straftaten aufzudecken oder zu unterbinden und Gesetzgeber, die versuchen, die Nutzung zu regulieren, ein Wettrennen. Den Strafverfolgungsbehörden stellen sich zahlreiche Herausforderungen, etwa die Ermittlung von Straftäter:innen, das Fehlen eines rechtlichen Rahmens für die Strafverfolgung sowie von Instrumenten und Ausbildung um Straftaten vorzubeugen oder sie zu unterbinden. Um die Beziehung zwischen Kryptowährungsdelikten und Ermittlungs- und Präventionsmethoden zur digitalen Disruption besser zu verstehen, wird der Forschungsstand analysiert. Ziel ist es, die Praxis, z. B. die Polizei, bei Prävention, Störung und Reduzierung von Delikten zu unterstützen. Die Ergebnisse informieren über Kategorien und Umfang illegaler Aktivitäten sowie den Einfluss von Kryptowährungsmärkten auf Kriminalität, beides wichtige Aspekte für Strafverfolgungsbehörden. Außerdem wurden Ermittlungs- und Präventionsmethoden für digitale Disruption aus der Sicherheitsforschung identifiziert; diese werden hinsichtlich Empfehlungen für weitere Forschung diskutiert. Ebenso wird der Einfluss illegaler Aktivitäten als Treiber des Kryptowährungsmarktes diskutiert. Es wird angenommen, dass die illegale Nutzung von Kryptowährungen zwar zahlenmäßig zunimmt, das Volumen im Verhältnis zum gesamten Markt jedoch abnimmt. Allerdings ist der Kenntnisstand über Umfang, Ausmaß und Veränderungsrate in den verschiedenen Deliktsbereichen uneinheitlich, und es besteht noch kein Konsens über ein einheitliches Berechnungsmodell. Der Text schließt mit einer Reihe von Empfehlungen.

Inácio, Igor de Santana

Esta tese oferece uma análise dos fundamentos da Decentralized Finance, particularmente das tokens não fungíveis e dos desafios que estas inovações representam para o arcabouço legal da União Europeia contra o branqueamento de capitais e financiamento do terrorismo. Por um lado, a tese irá analisar as mudanças que estas inovações podem trazer ao mercado da arte e à indústria criativa. Por outro lado, centrarse-á nos riscos de crime financeiro que advêm da maior facilidade em ocultar os produtos do crime na blockchain.

Nosipho Mthembu, Kazeem Abimbola Sanusi, Joel Hinaunye Eita

The study investigates the effects of stock market volatility and cybercrime on cryptocurrency returns in the South African economy. Daily time series data on four different types of cryptocurrencies (Bitcoin, Ethereum, Tether, and BMB) were employed. The data covers the period from 1 January 2019–31 December 2021. The study employed the dynamic conditional correlation (DCC GARCH) and Bayesian liner regression model to investigate time-varying correlations among the variables. Empirical findings suggest that stock market volatility has a positive impact on the returns of BNB, Bitcoin, and Ethereum. However, it has a negative impact on Tether. Expectedly, cybercrime poses negative impacts on the returns of BNB, Bitcoin, and Ethereum but could be said to have no impact on the returns of Tether. The study concludes that ongoing efforts to reduce cybercrime activities need to be strengthened to further the use of digital currencies.

Authors unavailable

No abstract is available for this record.

Zheng Yang, Chao Yin, Junming Ke, Tien Tuan Anh Dinh · 5 authors

Pooled mining has become the most popular mining approach in the Bitcoin system, which can effectively reduce the variance of the block generation reward of participants. The security of pooled mining depends on whether it is incentive compatible, that is, an honest participant will get a reward proportional to his work. Recent attacks on mining pools, for example, Block Withholding, Fork After Withholding, and Power Adjusting Withholding (PAW) attacks, show that malicious participants may undermine the revenue of the honest pools and receive an unfair share of the mining reward. This paper shows that the security of Bitcoin is even worse than what the recent attacks demonstrated. We describe an attack called Fork Withholding Attack under a Protection Racket (FWAP), in which the mining pool pays the attacker for withholding a fork. Our insight is that the mining pools under forking attacks have incentives to pay in exchange for not being forked. The attacker and the paying pool negotiate how much to be paid, and we show that it is possible for both the attacker and the paying pool to earn higher rewards at the expense of the other pools. In particular, our formal analysis and simulation demonstrate that the payer and the FWAP attacker can get up to 1.8 × and 3.8 × of extra reward as in PAW, respectively. Furthermore, FWAP can escape from the “miners’ dilemma’’ when two FWAP attackers attack each other under some circumstances. We also propose simple approaches that serve as the first step towards preventing the FWAP attack.

István Ambrus, Kitti Mezei

Abstract Money laundering is one of the most important criminal offences today, perceived in the context of economic operation. Nevertheless, money laundering is a constantly changing phenomenon that is also influenced by the latest technological advancements. In this study, our aim is, after briefly outlining the phenomenon of money laundering, to review the new statutory definition(s) and those assessment criteria that may also be of significance for legal practice in this context from 2021 onwards in Hungary. Subsequently, we will describe the current challenges of cryptocurrencies regarding the new Hungarian and EU legislation on money laundering. The method we use is criminal law-dogmatic and retrospective analysis. The analysis concluded that the Hungarian legislator has significantly broadened the scope of money laundering, and a much wider spread of this offence is predicted for the future.

Abhishek Thommandru, Benarji Chakka

Abstract Summary The COVID-19 pandemic experience has driven us to rely on technology so much on the development and expansion of technology, including cashless transactions. Criminal groups may become more interested in electronic payments and virtual currencies because of increased traffic in these areas. When comparing the second half of the 2019 to the first half of the 2020, the number of fraudulent card transactions increased by 11.4%. New developments in virtual currency trading regulations, including the digital finance package, which includes, among other things, a draught regulation from the European Parliament and an amended act to combat money laundering and terrorist financing, among others. For the reasons stated above, these regulations may lead to a virtual currency market collapse and the withdrawal of investors and the siphoning of money into Asian markets as a result. The current regulations are a manifestation of total regulation and do not encourage technological advancement.

Ian W. Gray, Jack Cable, Benjamin P. Brown, Vlad Cuiujuclu · 5 authors

Ransomware operations have evolved from relatively unsophisticated threat actors into highly coordinated cybercrime syndicates that regularly extort millions of dollars in a single attack. Despite dominating headlines and crippling businesses across the globe, there is relatively little in-depth research into the modern structure and economics of ransomware operations.In this paper, we leverage leaked chat messages to provide an in-depth empirical analysis of Conti, one of the largest ransomware groups. By analyzing these chat messages, we construct a picture of Conti’s operations as a highly-profitable business, from profit structures to employee recruitment and roles. We present novel methodologies to trace ransom payments, identifying over $80 million in likely ransom payments to Conti and its predecessor – over five times as much as in previous public datasets. As part of our work, we will publish a dataset of 666 labeled Bitcoin addresses related to Conti and an additional 75 Bitcoin addresses of likely ransom payments. Future work can leverage this case study to more effectively trace – and ultimately counteract – ransomware activity.

Zhengjie Huang, Yunyang Huang, Peng Qian, Jianhai Chen · 5 authors

Bitcoin is one of the decentralized cryptocurrencies powered by a peer-to-peer blockchain network. Parties who trade in the bitcoin network are not required to disclose any personal information. Such property of anonymity, however, precipitates potential malicious transactions to a certain extent. Indeed, various illegal activities such as money laundering, dark network trading, and gambling in the bitcoin network are nothing new now. While a proliferation of work has been developed to identify malicious bitcoin transactions, the behavior analysis and classification of bitcoin addresses are largely overlooked by existing tools. In this paper, we propose BAClassifier, a tool that can automatically classify bitcoin addresses based on their behaviors. Technically, we come up with the following three key designs. First, we consider casting the transactions of the bitcoin address into an address graph structure, of which we introduce a graph node compression technique and a graph structure augmentation method to characterize a unified graph representation. Furthermore, we leverage a graph feature network to learn the graph representations of each address and generate the graph embeddings. Finally, we aggregate all graph embeddings of an address into the address-level representation, and engage in a classification model to give the address behavior classification. As a side contribution, we construct and release a large-scale annotated dataset that consists of over 2 million real-world bitcoin addresses and concerns 4 types of address behaviors. Experimental results demonstrate that our proposed framework outperforms state-of-the-art bitcoin address classifiers and existing classification models, where the precision and F1-score are 96% and 95%, respectively. Our implementation and dataset are released, hoping to inspire others.

Stručni konsultant rane biznis faze (startap faze) u IT industriji, Ivan Ivljanin

What led to the meteoric growth and popularity of cryptocurrencies, primarily Bitcoin? What concepts preceded the development of modern cryptocurrencies? What is blockchain and what is the architecture of different distributed public ledgers? What is the use value of digital money in everyday transactions and what is the use value in international trade exchange? This paper tries to answer the above questions and decipher the highly complex technical jargon that usually accompanies the topic of digital money.