With the boom of cryptocurrency and its concomitant financial risk concerns, detecting fraudulent behaviors and associated malicious addresses has been drawing significant research effort. Most existing studies, however, rely on the full history features or full-fledged address transaction networks, both of which are unavailable in the problem of early malicious address detection and therefore failing them for the task. To detect fraudulent behaviors of malicious addresses in the early stage, we present Evolve Path Tracer, which consists of Evolve Path Encoder LSTM, Evolve Path Graph GCN, and Hierarchical Survival Predictor. Specifically, in addition to the general address features, we propose Asset Transfer Paths and corresponding path graphs to characterize early transaction patterns. Furthermore, since transaction patterns change rapidly in the early stage, we propose Evolve Path Encoder LSTM and Evolve Path Graph GCN to encode asset transfer path and path graph under an evolving structure setting. Hierarchical Survival Predictor then predicts addresses' labels with high scalability and efficiency. We investigate the effectiveness and generalizability of Evolve Path Tracer on three real-world malicious address datasets. Our experimental results demonstrate that Evolve Path Tracer outperforms the state-of-the-art methods. Extensive scalability experiments demonstrate the model's adaptivity under a dynamic prediction setting.
Raffaele Trequattrini, Matteo Palmaccio, Mario Turco, Alberto Manzari
Abstract This paper proposes a systematic literature review emphasising scholars' view on the impact of the adoption of blockchain technologies to fight corruption. Providing a deep understanding of the state of the art, the paper drafts implications and valuable insights to address future research. The connection of anticorruption policies and blockchain technologies has been investigated using Scopus database and ABS journal ranking. The importance assumed by anticorruption policies and the innovativeness of the blockchain technology, thanks to its characteristics of immutability, automatic timestamping and distributed architecture, needs to be investigated in an integrated perspective. This study provides for the first time a systematic connection among anticorruption practices and blockchain towards the lens of the business, management and accounting field, providing valuable implications, insights and emerging issues.
Jan 1, 2023·Proceedings of the 3rd International Conference on Law, Social Science, Economics, and Education, ICLSSEE 2023, 6 May 2023, Salatiga, Central Java, Indonesia
Virtual money or cryptocurrency has become a hot topic in electronic media discussions lately. Cryptocurrency is a form of intangible commerce that only exists in digital form and can be used in electronic transactions. This study aims to demonstrate that the Act Number 8 of 2010 concerning the Prev
The traditional currency cross-border circulation model has many problems in terms of efficiency, cost, and security.The private digital currencies represented by Bitcoin and Ethereum are flourishing and occupying an increasingly important position in cross-border payments.However, digital currencies themselves face great uncertainty and affect the stable operation of the global monetary system.In response, countries have started to develop CBDCs to enhance their financial inclusion and international competitiveness of their currencies with the advantages of digital currencies.However, the birth of new technologies often creates new problems, and CBDCs face a trade-off between privacy and transparency in their design, which can directly affect the supervision of CBDC funds and lead to CBDCs becoming a tool for financial crimes.This paper introduces the background and dynamics of CBDC development and the challenges it faces and combines existing relevant research and literature to propose countermeasures against CBDC financial crimes from several aspects: big data, artificial intelligence, and new regulation.Finally, future research directions in this field are proposed.
The purpose of this paper is to suggest the uses of a simulator to evaluate how vulnerable is a cryptocurrency. It is called “The Cryptocurrency Vulnerability Evaluator (CV-Evaluator)”. The main objective of the CV-Evaluator is to evaluate how vulnerable is a cryptocurrency in case of a deep financial crisis, war, inflation, unemployment, economic desgrowth, corruption, large trade and government deficit, natural disasters, or pandemic. Hence, our final target is to observe WHEN to buy or sell cryptocurrencies (Angel & McCabe, 2015) in the right timing under different circumstances and environments. It is based on the uses of different levels of risk through the visualization of a cube that keep in constant movement and warp stage all the time. Finally, we are using Bitcoin such as an experimental laboratory to test our simulator.
Contrasted with the boundless enthusiasm on crypto-X is the intense scepticism that others have when it comes to Bitcoin. Many people do not accept that Bitcoin can have any value independent of the backing of a nation-state. They think it is a scam, a Ponzi, a bubble, a fad, and a con. And they think it is a dangerous destabiliser for the status quo. Some also see the goals or delusions of their political rivals reflected in Bitcoin advocacy. Libertarians and Trump supporters and goldbugs distrustful of the monetary system and seeking to decentralise it. Paul Krugman’s New York Times opinion pieces on cryptocurrency and Bitcoin and, most importantly, the hundreds of thousands of words of comments posted by his readers in response to his articles are an interesting window onto these issues, including the political divide that separates Bitcoin advocates and some of their critics.
The purpose of this paper is twofold: (i) to investigate some of the main issues surrounding the classification of digital currencies, and (ii) to identify the accounting practices and standards tied to digital currencies. This paper discusses two different types of digital currencies, including: central bank digital currencies (CBDCs) and privately issued cryptocurrencies such as Bitcoin. The findings of this study suggest that current accounting standards do not precisely cover the accounting treatment of digital currencies, even though the estimated value of market capitalisation of cryptocurrency in 2022 was USD 200 billion. This conceptual paper identifies the imminent need for an accounting standard to provide guidance on the identification, classification, measurement, and presentation of digital currencies. In the interim, existing accounting standards can be amended to incorporate digital currencies to avoid inconsistent global accounting approaches.
In the evolving landscape of international trade, this comprehensive exploration delves into the paradigm shift enabled by smart contracts, challenging the traditional role of Documentary Credits (LCs). By prioritizing transparency, the article showcases how the integration of smart contracts revolutionizes proforma invoicing submission and offers a robust mechanism for scrutinizing over and under-invoicing—an entrenched tactic in Trade-Based Money Laundering (TBML). The innovative concept of introducing a bidding process within smart contracts opens doors for global participation, reducing entry barriers for startups and entrepreneurs, thereby transforming poverty into prosperity. These transformative mechanisms, rooted in blockchain technology, mark a compelling shift towards combatting TBML and fostering a more inclusive and dynamic global economy.
The primary objective of this research is to study the effectiveness of blockchain technology in preventing financial cybercrime. In this research, the researcher intends to know the effectiveness of blockchain technology in preventing financial cybercrime, the white-collar crime which is growing drastically globally. The researcher uses the primary method to collect the data. In this study, four different variables that influence financial cybercrime significantly are immutability, smart contract, distributed ledger technology and consensus algorithm. The data was collected from the targeted respondents which are accountants, IT experts and human resources. Statistical Package of the Social Sciences (SPSS) is being utilized to evaluate the relationship between the four variables which able to influence financial cybercrime. A total of 70 survey questionnaires were delivered to the targeted respondents via a convenience sampling strategy. Responses from 70 participants were entered into SPSS one by one to generate descriptive and inferential statistics. Financial cybercrime is positively correlated with immutability, smart contract, distributed ledger technology and consensus algorithms. As a result, the analysis of the collected data for this research rejects the null hypothesis, while supporting the alternative hypothesis. The conclusion that can derive from this research is that users and organizations should be aware of the financial cybercrime risks that take place around them and the importance to have vital tools that are not vulnerable to malicious attacks. This research creates awareness for users and companies on the usage of blockchain to prevent financial cybercrime.
Smart contracts have led to more efficient development in finance and healthcare, but vulnerabilities in contracts pose high risks to their future applications. The current vulnerability detection methods for contracts are either based on fixed expert rules, which are inefficient, or rely on simplistic deep learning techniques that do not fully leverage contract semantic information. Therefore, there is ample room for improvement in terms of detection precision. To solve these problems, this paper proposes a vulnerability detector based on deep learning techniques, graph representation, and Transformer, called GRATDet . The method first performs swapping, insertion, and symbolization operations for contract functions, increasing the amount of small sample data. Each line of code is then treated as a basic semantic element, and information such as control and data relationships is extracted to construct a new representation in the form of a Line Graph (LG), which shows more structural features that differ from the serialized presentation of the contract. Finally, the node information and edge information of the graph are jointly learned using an improved Transformer–GP model to extract information globally and locally, and the fused features are used for vulnerability detection. The effectiveness of the method in reentrancy vulnerability detection is verified in experiments, where the F1 score reaches 95.16%, exceeding state-of-the-art methods.
This paper quantifies mainstream media coverage of Bitcoin to understand how a once niche interest entered public culture. From 2011 to 2022, five key narratives are identified as criminality, culture, politics, price and technology. Price, politics, and culture have become more prominent in coverage while the technology narrative has waned. Coverage that is more political or cultural is associated with subsequently lower returns whereas the criminality narrative is associated with higher returns. Together this suggests that as narratives have become more mainstream, they have created additional demand, despite the negative association with criminal activity.
Oracles are software components that enable data exchange between siloed blockchains and external environments, enhancing smart contract capabilities and platform interoperability.Oracles play key roles in decentralized finance and blockchain applications in centralized finance.We find that integration into decentralized oracle networks is positively associated with key measures of economic activity such as Total Value Locked, triggered by positive network effects in adoption and usage.Our study reveals symbiotic gains from enhanced interoperability and network effects across protocols on a given chain and among integrated chains.Oracle integration appears to improve risk-sharing and mitigates contagion, increasing resilience during turbulent periods in crypto markets.Overall, oracles emerge as a crucial component to enable informational and economic integration in decentralized finance ecosystems.