Non-Fungible Token (NFT) is regarded as one of the important applications of blockchain technology. In this article, we propose an asset-backed securities (ABS) scheme that splits the complete NFT into a certain number of units, which are shared by multiple participants. On the one hand, ABS plans to promise high-value and long-term investment returns by enhancing the market liquidity of NFTs. On the other hand, securitized NFTs can participate in De-Fi as an automated market maker (AMM), just like AMM in alternative tokens. However, when a participant with a portion of the NFT tries to obtain full ownership of the NFT, the acquisition process may face some obstacles, including strategic bidding. Therefore, we proposed a game theory model and de- signed a novel NFT repurchase mechanism to overcome these obstacles. Our solution helps to successfully carry out the repurchase process at a reasonable price when issuing single-chip NFT asset-backed securities.
Валерія Аркадіївна Динту, В. А. Динту, Валерия Аркадиевна Дынту, Валерия Аркадиевна Дынту · 9 authors
The purpose of the article is to explain the use of cryptocurrency as a terrorist financing tool. This article has emphasized the ways, which terrorists appraise for being a reliable fundraising means and their adoption. Methodology. For the purposes of the study, the methods of scientific abstraction, synthesis, observation, generalization, as well as the method of induction of literature and legal documents were used to determine the features of bitcoin, promoting and preventing its use for terrorism financing. Results. The development of the Internet and electronic devices has radically changed all spheres of human life, including criminal activity. Digitalization has led to the improvement of ordinary crimes and the emergence of new types of crime, which, in principle, cannot exist without special digital electronic devices. Among the first implementers of new technologies were terrorists, who took advantage of digitalization to increase profitability. Thus, terrorists have now significantly increased their attention to cryptocurrency as a digital means of payment, namely Bitcoin. Bitcoin has a number of features that have attracted the attention of criminals as a way to evade responsibility for a crime. In particular, decentralization avoids the need for confirmation by a central authority, and pseudo-anonymity provides a certain level of anonymity. In addition, terrorists are aware that Bitcoin's confidentiality is extremely fragile and needs to be enhanced. The paper analyzes several ways to enhance anonymity, such as software that anonymizes traffic and prevents IP identification, peer-to-peer mixers, centralized mixing services (tumbler), and other approaches. It is worth emphasizing that for the fight against crime, the main issue is the de-anonymization of the Bitcoin owner/user, which allows the identification of the criminal. Currently, law enforcement agencies use direct and indirect de-anonymization, proliferation analysis, quantitative analysis, time analysis, and transactional network analysis, among others, to achieve the above goal, which are discussed in detail in this article. In addition, agencies around the world investigated and uncovered terrorist groups and their financial facilitators. Specifically, on August 13, 2020, the U.S. Department of Justice's Office of Public Affairs announced "the largest cryptocurrency seizure in the context of terrorism in history." To investigate the agenda, the legal documents of those investigations that contain information about the terrorist fund-raising mechanism were examined and analyzed. The legal documents revealed that these investigations used the aforementioned de-anonymization approaches.
We survey large-scale cryptocurrency thefts over the past decade, estimating the total value of stolen cryptocurrencies. We find that depending on when the cryptocurrency was converted to fiat, the stolen amounts are valued between $7 to $88 billion, with longer cryptocurrency holding periods corresponding to the larger estimate due to the market’s rising value. We also document that as the cryptocurrency market develops, the incidence of large-scale cryptocurrency thefts has also increased in both number and stolen values in recent years. Large-scale thefts can be attributed to security breaches accounting for 20 of the 30 thefts, human errors accounting for five, and agency problems arising from insider thefts accounting for the remaining five.
Diego Cagigas, Judith Clifton, Daniel Díaz‐Fuentes, Marcos Fernández Gutiérrez
Blockchain is heralded as being “the next big thing” that promises to radically transform society and the economy in near-future applications. While scholarly literature on blockchain has largely focused on bitcoin and cryptofinance, in recent years, a body of scholarship has started to emerge on blockchain in the public sector. The characteristics of blockchain have made it a promising technology to transform many activities related to public policy and public service provision, such as administrative processes, welfare provision and regulation practices. This article provides, to the best of our knowledge, the first systematic literature review of the use of blockchain across all the main public services. This systematic review identifies the public services most likely to be impacted by the introduction of blockchain. It also highlights the main potential benefits, costs and risks of blockchain for government, civil servants and citizens. Governments are found to benefit mainly from improvements in efficiency and traceability, while regulatory uncertainty and questions around scalability represent major costs and risks for them. Civil servants, the least studied actor in the literature, could benefit from blockchain through the reduction of red tape and improvements in coordination between agencies. Their lack of blockchain knowledge and skills represent a major cost as regards adoption. Regarding citizens, security and transparency are identified as being the most important benefits, while risks are mainly associated with data security concerns. The article concludes by noting several limitations in the literature and providing suggestions towards fruitful lines of research.
Since the inception of Bitcoin in 2009, the market of cryptocurrencies has grown beyond the initial expectations, as witnessed by the thousands of tokenised assets available on the market, whose daily trades amount to dozens of USD billions. The pseudonymity features of these cryptocurrencies have attracted the attention of cybercriminals, who exploit them to carry out potentially untraceable scams. The wide range of cryptocurrency-based scams observed over the last ten years has fostered the research on the analysis of their effects, and the development of techniques to counter them. However, doing research in this field requires addressing several challenges: for instance, although a few data sources about cryptocurrency scams are publicly available, they often contain incomplete or misclassified data. Further, there is no standard taxonomy of scams, which leads to ambiguous and incoherent interpretations of their nature. Indeed, the unavailability of reliable datasets makes it difficult to train effective automatic classifiers that can detect and analyse cryptocurrency scams. In this paper, we perform an extensive review of the scientific literature on cryptocurrency scams, which we systematise according to a novel taxonomy. By collecting and homogenising data from different public sources, we build a uniform dataset of thousands of cryptocurrency scams.We devise an automatic tool that recognises scams and classifies them according to our taxonomy.We assess the effectiveness of our tool through standard performance metrics.We also give an in-depth analysis of the classification results, offering several insights into threat types, from their features to their connection with other types. Finally, we provide a set of guidelines that policymakers could follow to improve user protection against cryptocurrency scams.
Shanqing Yu, Jie Jin, Yunyi Xie, Jie Shen · 5 authors
With the rapid growth of blockchain, an increasing number of users have been attracted and many implementations have been refreshed in different fields. Especially in the cryptocurrency investment field, blockchain technology has shown vigorous vitality. However, along with the rise of online business, numerous fraudulent activities, e.g., money laundering, bribery, phishing, and others, emerge as the main threat to trading security. Due to the openness of Ethereum, researchers can easily access Ethereum transaction records and smart contracts, which brings unprecedented opportunities for Ethereum scams detection and analysis. This paper mainly focuses on the Ponzi scheme, a typical fraud, which has caused large property damage to the users in Ethereum. By verifying Ponzi contracts to maintain Ethereum's sustainable development, we model Ponzi scheme identification and detection as a node classification task. In this paper, we first collect target contracts' transactions to establish transaction networks and propose a detecting model based on graph convolutional network (GCN) to precisely distinguishPonzi contracts. Experiments on different real-world Ethereum datasets demonstrate that our proposed model has promising results compared with general machine learning methods to detect Ponzi schemes.
Bitcoin is gaining traction as an alternative store of value. Its market capitalization transcends all other cryptocurrencies in the market. But its high monetary value also makes it an attractive target to cyber criminal actors. Hacking campaigns usually target an ecosystem’s weakest points. In Bitcoin, the exchange platforms are one of them. Each exchange breach is a threat not only to direct victims, but to the credibility of Bitcoin’s entire ecosystem. Based on an extensive analysis of 36 breaches of Bitcoin exchanges, we show the attack patterns used to exploit Bitcoin exchange platforms using an industry standard for reporting intelligence on cyber security breaches. Based on this we are able to provide an overview of the most common attack vectors, showing that all except three hacks were possible due to relatively lax security. We show that while the security regimen of Bitcoin exchanges is subpar compared to other financial service providers, the use of stolen credentials, which does not require any hacking, is decreasing. We also show that the amount of BTC taken during a breach is decreasing, as well as the exchanges that terminate after being breached. Furthermore we show that overall security posture has improved, but still has major flaws. To discover adversarial methods post-breach, we have analyzed two cases of BTC laundering. Through this analysis we provide insight into how exchange platforms with lax cyber security even further increase the intermediary risk introduced by them into the Bitcoin ecosystem.
A growing stream of research finds several relations between the economic growth and corruption. Government implements various strategies to diminish the corruption and also technology often plays a dominant role to face it. Among various technologies alterations, Block-chain technology that becomes an effective and efficient way to resolve these issues related to corruption. This paper represents a brief knowledge related to the Block-Chain technology as it is a kind of distributed database or public ledger of all transactions that have been executed and shared among participating parties. Each and every transaction in the public ledger is verified by a majority of the participants registered in the system. The possible risk related to current scenario and give brief idea for resolving that problem with the help of blockchain technology. Non-Governmental Organization (NGOs) which aim is to tackle some of the issues faced by the society. NGO faces difficulty in terms of maintaining and gaining the support from donors in terms of funds. In recent decades there have been multiple examples of corruption misconduct scandals impacting the public image and reputation of NGOs. It is clear that trust of the people in NGOs is affected adversely by such events. Doubts arise in terms of where does the donation ends up? Who is leading the organization? Is donated money are used in a proper direction? So as a part of it, a need is raised to solve such issues for the betterment of the society. For the above stated problem regarding management of funds in NGOs, we propose a solution by using the Blockchain technology among various technologies alteration available. Blockchain offers the way to eliminate the doubts by providing data security, immutability and transparency. So, Blockchain Technology can offer the NGO industry to regain the trust of public.
The criminal activities in India are increasing at a rapid rate. Many of these activities go unreported. Even after having an online portal for the police for storing FIRs and NCRs, most of the FIRs are handwritten as a traditional practice. In most of the cases, the complainant has to be present in the police station to file a cognizable offense. An effective system for e-governance was started in 2009 named Crime and Criminal Tracking Network and Systems (CCTNS) for the entire country. However, it is a centralized system for a particular state. Thus there is a need for a completely decentralized system for assuring that there is no central point of failure in the system and complaints are managed securely protected from unauthorized access. Our aim is to propose a blockchain-based solution to manage complaints against both cognizable and non-cognizable offenses. The FIR filed by the police will be encrypted, stored in the IPFS and hash is added to the blockchain network. If the police decide not to file the FIR under pressure or deny receiving any complaint, then the complainant will have strong proof against him/her as the complaint along with its timestamp was stored on the blockchain network. Having all the records stored in an immutable database would remove any chances of the FIR/NCR being tampered and going unnoticed.
Smart contracts empowered by blockchains often manage digital assets in a distributed and decentralized environment. People believe in smart contracts based on these new technologies. Unfortunately, malicious smart contacts, such as smart Ponzi scheme contracts (ponzitracts, for short), pose risk. Existing techniques detect ponzitracts by analyzing the code as well as a large amount of transaction data after time-consuming deployment. However, a conclusion based on transaction data can only be gotten after the damage has been caused. This paper proposes PonziDetector, a ponzitract detection technique that does not rely on transaction data. Behavior forest is introduced into PonziDetector to capture dynamic behaviors of smart contracts during interacting with them, which makes it possible to early detect ponzitracts. The empirical study demonstrates that PonziDetector, without transaction data, can improve the precision and the recall of the state-of-the-art to 94.6% and 93.0% respectively. This means that PonziDetector can avoid potential losses by early detecting ponzitracts.
The emergency of anonymous encrypted digital currency based on blockchain brings the rapid growth of financial crimes simultaneously. However, under the condition of Know Your Customer rules, the traditional rule-based filtering and supervised pattern recognition methods are mainly built, which does not apply to the scenario of anonymous encrypted digital currency. In this paper, we attempt to tackle this problem by constructing user graph from transactions and dividing the whole user graph into tightly connected communities and clustering similar communities into groups. Experimental results on bitcoin transaction datasets show that the proposed approach has higher than 92% precision and higher than 73% recall for identifying gambling and mining pool communities.
The application of blockchain has moved beyond cryptocurrencies, to applications such as credentialing and smart contracts. The smart contract allows ones to achieve fair exchange for values without relying on a centralized entity. However, as the smart contract can be automatically executed with token transfers, an attacker can seek to exploit vulnerabilities in smart contracts for illicit profits. Thus, this paper proposes a support vector machine (SVM)-based scanning system for vulnerabilities on smart contracts. Our evaluation on Ethereum demonstrate that we achieve a identification rate of over 90% based on several popular attacks.
The paper is devoted to the actual problem of ensuring privacy during performing transactions in distributed ledgers. We discuss various aspects of transaction privacy, as well as the specifics of setting the problem for distributed ledgers with two main models for representing participants' balances: the UTXO-model and the account model. Based on these results, we outline definitions and consider security properties of the main cryptographic primitives used for preserving the privacy of transactions: mixers, ring signatures, homomorphic encryption, and zero-knowledge proofs. We analyze well-known solutions for distributed ledgers based on the UTXO-model, such as Zcash, Monero, Zcoin, Dash, CoinShuffle, Verge, Grin, and others, as well as for systems based on the account model: DSC, Zether, Zeth, BlockMaze. Based on the comparison of advantages, disadvantages, and limitations for existing solutions, conclusions are drawn about the future development of distributed ledgers that ensure the privacy of transactions, and new research tasks are outlined.
This comprehensive overview of analysis techniques for illicit Bitcoin transactions addresses both technical, machine learning approaches as well as a non-technical, legal, and governance considerations. We focus on the field of ransomware countermeasures to illustrate our points.
ABSTRACT Unhackable. Immutable. Fraud‐proof. These terms are frequently used to describe cryptocurrencies and the blockchain technology that underpins them. Together, they imply that a high degree of safety accompanies cryptocurrencies and blockchain ledgers. But is this understanding supported by the facts, or is it more based on the promise and theoretical construction of blockchain and cryptocurrencies? To better answer this question, we have compiled and analyzed existing research on initial coin offerings, security offerings, blockchain hacks and thefts, and data breaches of blockchain‐based platforms and digital wallets. In contrast to the popular press, we find that in practice, blockchain and cryptocurrencies are more prone to malfeasance, fraud, and manipulation than is commonly understood. The security and trust provided by blockchain as a technology tool are only as secure as the underlying code that establishes the blockchain, and the value derived from cryptocurrencies is only as trustworthy as the entity developing the cryptocurrency. Neither are without their vulnerabilities. Skepticism and proper due diligence should be maintained for any entity looking to utilize blockchain technology or invest in cryptocurrencies.
Abstract Past international trade practices have been associated with opaque information flows that have hindered traceability and created hurdles in hassle‐free trade. Blockchain and allied technologies have been investigated as a panacea for the problems faced by supply chain and logistics industry. Network analysis also uncovered twenty types of legal and antisocial entities operating on bitcoin and provided a path for uncovering these antisocial entities. However, earlier works of literature have focused on limited aspects of a typical supply chain such as monitoring assets, securing traceability, data integrity negligence, and data access. To overcome such drawbacks, this article proposes permissioned Blockchain with relevant processes and functions to obtain a holistic framework for securing the supply chain and logistic operations. The efficacy of the proposed framework was demonstrated in the case study. Comparative study was performed with the existing frameworks where the proposed framework was found to be better at four counts compared on the basis of data integrity in supply chain, decentralized decision making and traceability. It was found that critical loopholes in a current supply chain can be overcome using the proposed framework.
The production of counterfeit money has a long history. It refers to the creation of imitation currency that is produced without the legal sanction of government. With the growth of the cryptocurrency ecosystem, there is expanding evidence that counterfeit cryptocurrency has also appeared. In this paper, we empirically explore the presence of counterfeit cryptocurrencies on Ethereum and measure their impact. By analyzing over 190K ERC-20 tokens (or cryptocurrencies) on Ethereum, we have identified $2,117$ counterfeit tokens that target 94 of the 100 most popular cryptocurrencies. We perform an end-to-end characterization of the counterfeit token ecosystem, including their popularity, creators and holders, fraudulent behaviors and advertising channels. Through this, we have identified two types of scams related to counterfeit tokens and devised techniques to identify such scams. We observe that over 7,104 victims were deceived in these scams, and the overall financial loss sums to a minimum of \$ 17 million (74,271.7 ETH). Our findings demonstrate the urgency to identify counterfeit cryptocurrencies and mitigate this threat.
Purpose The purpose of this paper is to investigate the role of cryptocurrencies in facilitating operations relating to modern slavery and specifically human trafficking. Over the past decade, law enforcement agencies and intergovernmental organisations have established mechanisms, including financial regulations, to curb and identify such operations. Regulation over conventional financial institutions has greatly aided in identifying cross-border and transregional trafficking operations. However, there remains concern over the role of cryptocurrencies in the modern trafficking enterprise. Design/methodology/approach This paper follows a review of the literature, discussing specific cases that have exposed the role of cryptocurrencies in facilitating human trafficking. This paper first presents a comprehensive discussion on the existing operational mechanism of organisations in human trafficking. Subsequently, it determines the potential use of cryptocurrencies in circumventing detection by law enforcement agencies. Findings This paper finds that existing controls have allowed law enforcement to identify illicit transactions concerning human trafficking through conventional financial institutions. However, the most effective mechanism of identifying such operations is becoming increasingly difficult with the use of cryptocurrencies. Although there are potential solutions to the issues, cryptocurrencies, and the anonymity they offer, have allowed criminal organisations to evade detection using a more active marketplace through the internet. Research limitations/implications Law enforcement agencies and regulators must take into account the nature of cryptocurrencies and the limitations of regulations on such global virtual assets. Instead, this paper’s findings suggest alternate methods, including regulation on exchanges, blockchain use for documentation and investments in detection technologies that allow identification of trafficking operations and forced labour. Originality/value This paper presents existing cases and growing concerns that cannot be quantified in the current circumstance. Further, the paper aims to specifically discuss the role of cryptocurrencies in the existing human trafficking supply chain, offering readers and law enforcement agencies a perspective into criminal organisations’ combination of conventional trafficking operations and modern technological resources. Further, it makes a recommendation to invest in detection mechanisms that are different from the conventional theory based on identification by “following the money”.
Liming Fang, Bo Zhao, Li Yang, Zhe Liu · 6 authors
The development of 5G has substantially increased the destructiveness of DoS/DDoS attacks because the data processing capability of computers has not been accordingly enhanced, and this contradiction creates a vulnerability for attackers to compromise a server by sending a massive data flow. in practical 5G circumstances, it is difficult to extract distinct features between malicious and benign massive data flows. This amplifies the difficulties of DoS/DDoS detection. Thus, precautions against DoS/DDoS attack in 5G are of great importance. in this article, we present a solution based on smart contracts and machine learning as a countermeasure against DoS/DDoS attacks in the 5G background by hiding a protected server in a blockchain network and flexibly restricting the scale of DoS/DDoS via transaction fees. We also leverage non-repudiation of smart contracts, analyzing users' malicious behavior of communication and executing punishment via smart contracts. Our scheme could effectively mitigate massive DoS/DDoS attacks in advance and dynamically punitively charge DoS/DDoS attacks. Compared to existing DoS/DDoS defense in 4G, our scheme offers numerous benefits, including making benign communication always dominate rational users and countering DoS/DDoS attacks before they are launched. Moreover, compared to common DoS/DDoS detection based on Ai, we consider the source trustworthiness of training samples and take measures to avoid backdoors where model trainers may compromise Ai models to launch DoS/DDoS attacks.