Code Will Tell: Visual Identification of Ponzi Schemes on Ethereum

Ethereum has become a popular blockchain with smart contracts for investors nowadays. Due to the decentralization and anonymity of Ethereum, Ponzi schemes have been easily deployed and caused significant losses to investors. However, there are still no explainable and effective methods to help investors easily identify Ponzi schemes and validate whether a smart contract is actually a Ponzi scheme. To fill the research gap, we propose PonziLens, a novel visualization approach to help investors achieve early identification of Ponzi schemes by investigating the operation codes of smart contracts. Specifically, we conduct symbolic execution of opcode and extract the control flow for investing and rewarding with critical opcode instructions. Then, an intuitive directed-graph based visualization is proposed to display the investing and rewarding flows and the crucial execution paths, enabling easy identification of Ponzi schemes on Ethereum. Two usage scenarios involving both Ponzi and non-Ponzi schemes demonstrate the effectiveness of PonziLens

The Internet of Money between Anonymity and Publicity: Legal Challenges of Distributed Ledger Technologies in the Crypto Financial Landscape

This research project focuses on the impacts exerted by the tech schemes behind virtual currencies on the EU framework to prevent the misuse of the financial system and it aims to explore legal challenges posed in the IoM landscape by the double-edged nature of DLTs as both transparency and privacy-oriented. On the one hand, it plans to identify effective legislative and regulatory measures to ensure crypto accountability from an AML/CFT standpoint, as well as to assess the relevant role of pseudonymity. On the other hand, it pursues to discover innovative legal approaches to secure AML/CFT active cooperation in the crypto ecosystem(s), to the end of mitigating anonymity and traceability concerns while respecting both the value of publicity and transparency in the law and the conceptual origin of the crypto economy

A critical review on Blockchain assessment initiatives: a technology evolution viewpoint

Blockchain is considered as a major emerging technology that is having an everincreasing spread both in industrial and academic contexts. As the usage of blockchain keeps increasing, a fourth generation of blockchain platforms is being proposed. Thus, applications of blockchain have evolved towards wider scopes than cryptocurrency and asset management. In this context, it is important for practitioners to have deep understanding of various blockchain assessment initiatives. Therefore, this work discusses blockchain assessment initiatives from a technology evolution viewpoint. Furthermore, a mapping was conducted to identify factors that impact blockchain initiatives, synthesize available evidence, and identify gaps between relevant approaches available in the literature. As a result, nine selected works were analyzed based on applicability, research approach, assessment process, blockchain adoption process, and blockchain waves. The findings can help practitioners to understand the main assessment factors that undermine blockchain implementations.publishedVersio

Detection Of Insider Attacks In Block Chain Network Using The Trusted Two Way Intrusion Detection System

For data privacy, system reliability, and security, Blockchain technologies have become more popular in recent years. Despite its usefulness, the blockchain is vulnerable to cyber assaults; for example, in January 2019 a 51% attack on Ethereum Classic successfully exposed flaws in the platform's security. From a statistical point of view, attacks represent a highly unusual occurrence that deviates significantly from the norm. Blockchain attack detection may benefit from Deep Learning, a field of study whose aim is to discover insights, patterns, and anomalies within massive data repositories. In this work, we define an trusted two way intrusion detection system based on a Hierarchical weighed fuzzy algorithm and self-organized stacked network (SOSN) deep learning model, that is trained exploiting aggregate information extracted by monitoring blockchain activities. Here initially the smart contract handles the node authentication. The purpose of authenticating the node is to ensure that only specific nodes can submit and retrieve the information. We implement Hierarchical weighed fuzzy algorithm to evaluate the trust ability of the transaction nodes. Then the transaction verification step ensures that all malicious transactions or activities on the submitted transaction by self-organized stacked network deep learning model. The whole experimentation was carried out under matlab environment. Extensive experimental results confirm that our suggested detection method has better performance over important indicators such as Precision, Recall, F-Score, overhead

The Open Legal Challenges of Pursuing AML/CFT Accountability within Privacy-Enhanced IoM Ecosystems

This research paper focuses on the interconnections between traditional and cutting edge technological features of virtual currencies and the EU legal framework to prevent the misuse of the financial system for money laundering and terrorist financing purposes. It highlights a set of Anti-Money Laundering and Counter-Terrorist Financing (AML/CFT) challenges brought about in the Internet of Money (IoM) landscape by the double-edged nature of Distributed Ledger Technologies (DLTs) as both transparency and privacy oriented. Special attention is paid to inferences from concepts such as pseudonymity and traceability; this contribution explores these notions by relating them to privacy enhancing mechanisms and blockchain intelligence strategies, while heeding both core elements of the present AML/CFT obliged entities' framework and possible new conceptualizations. Finally, it identifies key controversies and open questions as to the actual feasibility of effectively applying the "active cooperation" AML/CFT approach to the crypto ecosystems

Blockchain Technology and The Current Discussion on Fraud

Blockchain has received increased attention from both the academic and practitioner worlds. Numerous papers have been written on how blockchain works and its potential applications. However, few studies have focused on fraudulent activities on blockchain. The purpose of this study is to understand common issues and scams related to blockchain. A literature review was conducted to identify top security issues on blockchain. In addition, we collected tweets on blockchain fraud discussion from November 6, 2018 to December 31, 2008. The results of tweets analysis show that the most frequently mentioned words in tweets include scams, crypto/cryptocurrency, ICO, Bitcoin, Ethereum,combat/fight, Asia, Japan, and Germany. The top mentioned sentiment words include scam, combat, guilty, prevent,solution, tired, and fake. In addition, a sentiment analysis shows that the majority of the tweets (69%) on the discussion on blockchain fraud are negative. The findings also shows the majority of top influencers of the topic are the companies that have developed blockchain-based platforms/applications

Decentralized Finance – A Systematic Literature Review and Research Directions

Decentralized Finance (DeFi) is the (r)evolutionary movement to create a solely code-based, intermediary-independent financial system—a movement which has grown from $4bn to$104bn in assets locked in the last three years. We present the first systematic literature review of the yet fragmented DeFi research field. By identifying, analyzing, and integrating 83 peer-reviewed DeFi-related publications, our results contribute fivefold. First, we confirm the increasing growth of academic DeFi publications through systematic analysis. Second, we frame DeFi-related literature into three levels of abstraction (micro, meso, and macro) and seven subcategories. Third, we identify Ethereum as the blockchain in main academic focus. Fourth, we show that prototyping is the dominant research method applied whereas only one paper has used primary research data. Fifth, we derive four prioritized research avenues, namely concerning i) DeFi protocol interaction and aggregation platforms, ii) decentralized off-chain data integration to DeFi, iii) DeFi agents, and iv) regulation

Blockchain Agency Theory

Longstanding assumptions underlying strategic alliances, such as agency theory, are actively being revoked by dynamics in the new economy. The mechanism of inter-firm cooperation is increasingly being altered by radical developments in blockchains and artificial intelligence among other technologies. To capture and address this shift, this review takes a problematisation approach and focuses wholly on the pertinence of agency theory. First, it begins by acknowledging the established corpus in the area before, second, appraising the seven long-held assumptions in the principal-agent relationship encompassing (1) self-interest, (2) conflicting goals, (3) bounded rationality, (4) information asymmetry, (5) pre-eminence of efficiency, (6) risk aversion and (7) information as a commodity. Third, to add a fresh perspective, the review proceeds to proffer seven assumptions to advance a novel ‘Blockchain Agency Theory’ that would better describe new attributes and relaxed agency behaviour in blockchain alliances. These counter assumptions are (1) common interests, (2) congruent goals, (3) unbounded rationality, (4) information symmetry, (5) smart contracts, (6) mean risk and (7) information availability. In the fourth part, the prior audience of principals and agents is appraised and this culminates into, fifth, a consideration of a new audience of blockchain agency in algocratic environments. Altogether, the seven new assumptions extend and provoke new agency thinking among scholars and blockchain practitioners alike