Blockchain technology has applications that can revolutionize political and economic governance. Although most of the academic literature on blockchain has focused on Bitcoin, there is a need to look at the feasibility of new humanitarian applications. This study will proceed in two steps. First, it surveys current theoretical and practical work on how blockchain can be used to help protect the human rights of migrants and refugees, primarily through creation of digital identities. Then it conducts a critical examination of two major cases: the Building Blocks initiative by the World Food Programme in Jordan and the Rohingya Project. We find that blockchain can be useful in empowering vulnerable individuals, but the empowerment of organizations creates potential human rights risks, such as the infringement of privacy and discrimination. Therefore, adequate safeguards should be in place to ensure that blockchain initiatives meet their true purposes of protecting the most vulnerable groups.
Nowadays, with the massive development of technologies, documents are usually made, modified and published digitally. Unlike paper documents, digital documents are easily falsified, and it is difficult to verify the authenticity of these advanced documents in effective and fast ways. Mushaf Al-Quran is one of the most sensitive digital documents that deserves to be preserved due to the divine messages it carries. There is no way to maintain an immutable document, as today's blockchain technology has proven. Therefore, to take advantage of blockchain technology, this article presents a decentralized web application (dApp) to authenticate and verify the digital Mushaf based on smart contracts and the Ethereum network. The results show the efficiency of the blockchain technology in preserving immutable documents and its effectiveness in protecting and proving the authenticity of the digital Mushaf Al-Quran.
Min-Yuh Day, Pei-Tz Chiu, Yung-Wei Teng, Chao-Lin Liu
Anti-money laundering involving cryptocurrencies has become a popular research topic in recent years. Moreover, constructing a knowledge graph of cryptocurrency anti-money laundering in a small sample of judgments to prevent cryptocurrency money laundering has become an essential issue for an improved understanding of the relationship between crime patterns and emerging financial technologies. The research method of this study is that we conducted a named entity recognition task and identified the key relation types to construct a cryptocurrency anti-money laundering knowledge graph (KG). Accordingly, we developed the âJudicia17,â a key relation type for cryptocurrency anti-money laundering KG. The contribution of this study is that the proposed âJudica17â relation types of cryptocurrency anti-money laundering KG can be applied to construct a legal knowledge graph.
In our rapidly globalizing and digitalizing world, data transfer can be done quickly in multimedia, communication, computer systems, etc. On the other hand, a blockchain database is a technology that allows us to transfer assets such as digital money that we attribute value to. This technology, which eliminates centralization and distributes reliability and transparency among all users, is also known as the technology under virtual currencies such as Bitcoin and Ethereum. El-Salvador is the first country to accept Bitcoin as a legal currency. It is one of the most fundamental issues to wonder how this will affect the economy of El-Salvador and the spread of financial services to all members of society. In this study, it is examined how the process of accepting Bitcoin as legal money has an effect on the economy of El-Salvador and the percentage of people's access to financial services. Although there is not a great background to make an empirical assessment on the subject, it seems that a large part of the society has started to use Bitcoin through the official mobile application of the state. It is seen that even citizens who did not have a bank account before can access financial services with this method. In addition, the rapid increase in the investments coming to the country due to the tax advantages provides a great added value for the country's economy.
In view of the increasingly serious problem of money laundering crime in the blockchain industry, the existing solutions in this scenario can not be applied to reality, or there is a high false positive rate and false negative rate, a method based on weighted sampling neighborhood nodes is designed to find and analyze the implied interrelationship in the data between blockchain transaction features, and learn more effective aggregate input features in the local neighborhood of nodes through model training. Good results have been achieved on the public data set, which verifies the effectiveness of the model in the field of blockchain abnormal transaction detection. Moreover, it provides an idea of modelling transaction entity data by using graph neural network structure for the field of financial data transactions such as anti-money laundering monitoring.
We present a novel way for cryptocurrency miners to manipulate the effective interest-rate on loans or deposits they make on decentralized finance (DeFi) platforms by manipulating difficulty-adjustment algorithms (DAAs) and changing the block-rate. This presents a new class of strategic manipulations available to miners.
Cryptocurrency has become ubiquitous and is evolving constantly. The question is if our legal framework is catching up with it. Therefore, this article analyzes the arguments on the legitimacy and legality of cryptocurrency in order to emphasize the relation between corruption and cryptocurrency. The research has enlightened some cogent arguments on the possibility of perpetrators committing corruption acts through cryptocurrency. These arguments basically refer to some of the unique characteristics of cryptocurrency such as the quick value fluctuation, the difficulties in tractability and the lacking current legislation. The unique features of it may headline cryptocurrency as an immensely attractive environment for corruption activities. Hence the world has already faced some tangled scamming scandals with cryptocurrency specified herein. Therefore, the aim of this article is to highlight the possibility for corruption acts to be committed through cryptocurrency as a form of corruption unknown before.
Bitcoin P2P networking is especially vulnerable to networking threats because it is permissionless and does not have the security protections based on the trust in identities, which enables the attackers to manipulate the identities for Sybil and spoofing attacks. The Bitcoin node keeps track of its peerâs networking misbehaviors through ban scores. In this paper, we investigate the security problems of the ban-score mechanism and discover that the ban score is not only ineffective against the Bitcoin Message-based DoS (BM-DoS) attacks but also vulnerable to the Defamation attack as the network adversary can exploit the ban score to defame innocent peers. To defend against these threats, we design an anomaly detection approach that is effective, lightweight, and tailored to the networking threats exploiting Bitcoinâs ban-score mechanism. We prototype our threat discoveries against a real-world Bitcoin node connected to the Bitcoin Mainnet and conduct experiments based on the prototype implementation. The experimental results show that the attacks have devastating impacts on the targeted victim while being cost-effective on the attacker side. For example, an attacker can ban a peer in two milliseconds and reduce the victimâs mining rate by hundreds of thousands of hash computations per second. Furthermore, to counter the threats, we empirically validate our detection countermeasureâs effectiveness and performances against the BM-DoS and Defamation attacks.
Jinho Choi, Jaehan KIM, Minkyoo Song, Hanna KIM · 8 authors
Cryptocurrency abuse has become a critical problem. Due to the anonymous nature of cryptocurrency, criminals commonly adopt cryptocurrency for trading drugs and deceiving people without revealing their identities. Despite its significance and severity, only few works have studied how cryptocurrency has been abused in the real world, and they only provide some limited measurement results. Thus, to provide a more in-depth understanding on the cryptocurrency abuse cases, we present a large-scale analysis on various Bitcoin abuse types using 200,507 real-world reports collected by victims from 214 countries. We scrutinize observable abuse trends, which are closely related to real-world incidents, to understand the causality of the abuses. Furthermore, we investigate the semantics of various cryptocurrency abuse types to show that several abuse types overlap in meaning and to provide valuable insight into the public dataset. In addition, we delve into abuse channels to identify which widely-known platforms can be maliciously deployed by abusers following the COVID-19 pandemic outbreak. Consequently, we demonstrate the polarization property of Bitcoin addresses practically utilized on transactions, and confirm the possible usage of public report data for providing clues to track cyber threats. We expect that this research on Bitcoin abuse can empirically reach victims more effectively than cybercrime, which is subject to professional investigation.
Abstract Bitcoin mining is not only the fundamental process to maintain Bitcoin network, but also the key linkage between the virtual cryptocurrency and the physical world. A variety of issues associated with it have been raised, such as network security, cryptoasset management and sustainability impacts. Investigating Bitcoin mining from a spatial perspective will provide new angles and empirical evidence with respect to extant literature. Here we explore the spatial distribution of Bitcoin mining through bottom-up tracking and geospatial statistics. We find that mining activity has been detected at more than 6000 geographical units across 139 countries and regions, which is in line with the distributed design of Bitcoin network. However, in terms of computing power, it has demonstrated a strong tendency of spatial concentration and association with energy production locations. We also discover that the spatial distribution of Bitcoin mining is dynamic, which fluctuates with diverse patterns, according to economic and regulatory changes.
Bitcoin plays a major role in digital online transactions with decentralized scattered Peer-to-Peer systems. Cryptocurrency framework permits individuals to exchange with proxy addresses in Fraternize services. Nowadays, Bitcoin users have been increasing rapidly due to various Fraternize services. Due to this, some illicit activities were happening by creating unknown addresses. We surveyed machine learning algorithms like Decision Tree and Random Forest to classify illicit transactions in the Bitcoin network which helps to improve True Positive rate (TPR), and also reviewed various Fraternize services to identify proxy addresses and trace the ownership of Bitcoin transactions. Furthermore, examines the challenges of tracing the proxy addresses in the Bitcoin ecosystem after fund transaction. For further implementation, Bitcoin Transaction Datasets were acquired from Kaggle.
Pedro Bustamante, Meina Cai, Marcela Gomez, Colin Harris · 13 authors
Studies of blockchain governance can be divided into analyses of the governance of blockchains (such as rules and power dynamics within a given network) and governance by blockchains (such as how blockchains can be implemented to improve self-governance of community-based peer production networks). Less emphasis has been placed on applications of distributed ledgers to public sector governance. Our review clarifies that the decentralization and distributive features that enable blockchains to link up loosely connected private organizations and public agencies to improve efficiency and transparency of government transactions. However, most blockchain applications lack clear advantages over the conventional digital recording of information. In addition, our review highlights that blockchain applications in public sector governance are potentially vast, though in most instances, the existing applications have not extended much beyond limited-scale pilots. We conclude with a call for the construction of indexes of public sector implementations of blockchains, as none yet exist, as well as for additional research to understand why governments have not deployed blockchains more widely.
Abstract Elliptic dataâone of the largest Bitcoin transaction graphsâhas admitted promising results in many studies using classical supervised learning and graph convolutional network models for anti-money laundering. Despite the promising results provided by these studies, only few have considered the temporal information of this dataset, wherein the results were not very satisfactory. Moreover, there is very sparse existing literature that applies active learning to this type of blockchain dataset. In this paper, we develop a classification model that combines long-short-term memory with GCNâreferred to as temporal-GCNâthat classifies the illicit transactions of Elliptic data using its transactionâs features only. Subsequently, we present an active learning framework applied to the large-scale Bitcoin transaction graph dataset, unlike previous studies on this dataset. Uncertainties for active learning are obtained using Monte-Carlo dropout (MC-dropout) and Monte-Carlo based adversarial attack (MC-AA) which are Bayesian approximations. Active learning frameworks with these methods are compared using various acquisition functions that appeared in the literature. To the best of our knowledge, MC-AA method is the first time to be examined in the context of active learning. Our main finding is that temporal-GCN model has attained significant success in comparison to the previous studies with the same experimental settings on the same dataset. Moreover, we evaluate the performance of the provided acquisition functions using MC-AA and MC-dropout and compare the result against the baseline random sampling model.
2017 is the year when the cryptocurrencies came into limelight with the primary trading in bitcoin being featured on a mainstream market in Chicago, Since then many people started investing into bitcoins or at least wanting to know about bitcoin, mostly including the people from the software industry. In this article it is clearly defined in a stepwise order using meaningful pictures and figures, from the very beginning of cryptocurrencies to the technology behind bitcoin, that is the blockchain technology. Most people do not trust in the security of trading in cryptocurrencies, but after understanding the working of Blockchain one would definitely believe in the technical security of using a cryptocurrency but the financial reasoning to investment in cryptocurrencies is a whole another story.
Abstract In shaping the Internet of Money, the application of blockchain and distributed ledger technologies (DLTs) to the financial sector triggered regulatory concerns. Notably, while the user anonymity enabled in this field may safeguard privacy and data protection, the lack of identifiability hinders accountability and challenges the fight against money laundering and the financing of terrorism and proliferation (AML/CFT). As law enforcement agencies and the private sector apply forensics to track crypto transfers across ecosystems that are socio-technical in nature, this paper focuses on the growing relevance of these techniques in a domain where their deployment impacts the traits and evolution of the sphere. In particular, this work offers contextualized insights into the application of methods of machine learning and transaction graph analysis. Namely, it analyzes a real-world dataset of Bitcoin transactions represented as a directed graph network through various techniques. The modeling of blockchain transactions as a complex network suggests that the use of graph-based data analysis methods can help classify transactions and identify illicit ones. Indeed, this work shows that the neural network types known as Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT) are a promising AML/CFT solution. Notably, in this scenario GCN outperform other classic approaches and GAT are applied for the first time to detect anomalies in Bitcoin. Ultimately, the paper upholds the value of publicâprivate synergies to devise forensic strategies conscious of the spirit of explainability and data openness.
Financial institutions opting for blockchain technology raise controversy about how this new technology can disrupt the traditional banking sector. Many issues like a decentralized system with no middlemen and untrusted parties pose serious threats to the banking system. Hence, there is a serious need to do research on the impact of blockchain on financial institutions, especially in the banking sector, to understand the influence of blockchain as a disruptor and a technology that is revolutionizing the banking sector. The chapter will explain the concepts and role of blockchain in the banking domain. Secondly, the ongoing criticism of the blockchain as a disruptor in the banking domain is answered in this chapter. Third, the role of blockchain in the transformation of the banking sector is discussed by explaining the blockchain process in the key banking services.
Blockchain and distributed ledger technologies are disrupting the world as we know it. Cryptocurrencies are increasingly been adopted not only by a large number of retail investors but financial institutions and even countries are embracing them. Nonetheless, there is a significant number and types of cryptocurrencies and, their treatment will likely depend on their legal status, use, and nature. Some jurisdictions may equate the legal status of cryptocurrencies to commodities or property, others may consider them to be digital currencies or legal tenders, while others may treat them as securities, financial instruments, or as a different asset class such as digital assets. Consequently, countries may regulate a cryptocurrency in different legal categories and might be overseen by a range of authorities depending on their use case and nature. This article aspires to shed some light on legal grey areas by studying how cryptocurrencies are regulated in a variety of jurisdictions and how their legal status is defined.
The chapter focuses on robustness of blockchain technology for recording a chain of transactions and maintenance of data. The initial sections of the chapter explain basic concepts like cryptography, double-entry ledger, cryptographic hashing, etc. that have been used in the development of blockchain technology. The authors explain the functioning of blockchain and its advantages in terms of time- stamped, immutable records. Blockchain represents a chain of transactions in the form of blocks that are connected through a hash unique to each block. Blockchain offers solutions to many real-world problems like recording the transactions and maintaining the records in a decentralized manner making the system efficient and yet ensuring transparency and safety. In subsequent sections, the authors discuss several use cases of blockchain in insurance and banking. The important applications include fraud detection and risk prevention, decentralized insurance and cheaper premiums, reinsurance, cross-border payments, trade finance, and compliance.
Cryptocurrencies differ from traditional financial assets as they are not governed by any higher authority, have no physical representation, are indefinitely divisible, and are not based on any tangible assets or country. While their popularity and use have surged over the years, they are still subject to an underlying risk. The purpose of this research is to investigate the regulatory approach for cryptocurrencies adopted around the world. To achieve the purpose of this research, extant literature is examined using a systematic literature review. Using a total of 49 Scopus indexed shortlisted articles, the extant literature on the various risks related to cryptocurrency and the regulatory approach adopted for the same was explored. The prior literature was classified into four thematic clusters of the regulatory approach to risks: pandemic, volatility, money laundering and cyber security. The findings suggest the regulations governing cryptocurrency are still at an infancy stage, and it still suffers from the challenge of limited transparency. The pandemic did not have a drastic impact on cryptocurrency. Cryptocurrencies are volatile in reaction to economic policy uncertainty and macroeconomic variables. To the best of the authorâs knowledge, this review paper is one of the few contributing to the gaps in the literature on the various risks and their associated regulatory approach to managing cryptocurrency.
The impact of globalization and the growing digitalization of the economy is becoming increasingly felt in the area of economic criminality, and we therefore believe that it is a matter of urgency to seek viable and effective solutions to manage this area of concerns, thus preventing the contamination of the borderline that currently separates legal and illegal technologies, depending on how they are regulated or not. In this light, the aim of our paper is to explore those instances in which blockchain accounting has the potential to be a viable solution to guarantee the security and legality of economic and financial transactions, thereby significantly mitigating the impact and frequency of economic criminality. The main objectives we pursue are to define the nature of the interrelation among the concept of blockchain, accounting and economic criminality and to evaluate the potential advantages of implementing blockchain technology in the accounting system. The main findings are a comprehensive mapping of the network that links blockchain technology, accounting and economic criminality employing the clustering method. These are likely to be of valuable assistance not only for the legislator, but also for the shaping of future research paths in this field and, last but not least, for an essential group of stakeholders such as computer scientists, accountants, auditors and national governments.