Recently, the right to privacy has become an important global issue, and laws are being enacted in different countries to ensure that citizens have control over how their data are stored and used. In this scenario, corporates face an increasing burden to comply with these laws, while ensuring that their business models and workflows are interrupted to as little a degree as possible. This article presents blockchain as a potential technology that can help users keep their data under their control and yet allow companies to responsibly access the data they need to function. It begins with an overview of blockchain as a technology and the properties that make it useful as a tool for privacy compliance. It then explores more niche fields, such as Zero Knowledge Proofs, and considers two industries where blockchain can be of benefit to consumers and corporates from a privacy standpoint.
Nowadays, it is almost impossible to imagine an effective legal system that is not somehow inspired by nominalistic ideas. However, the principle of monetary nominalism is not necessary in correlation with other higher principles, such as the principle of fairness, for example. Thus, legislators build and implement corrective instruments in legal acts, most of the time allowing legal subjects to choose and adapt those instruments to best fit their economic interests. In that context, (foreign) currency clauses are probably the most frequently used instrument. Those norms, when implemented in contract, prevent the negative effects of domestic currency depreciation through the denomination of the amount of debt in foreign currency. Whether we regard them as currency or not, cryptocurrencies are increasingly becoming an important part of our digitalized economic world. So, unless the legislature strictly limits or abolishes the freedom of will (the principle of party autonomy) in contract law by banning cryptocurrencies, contracting parties can hedge against domestic currency depreciation by pegging the amount of debt to the exchange rate of one of thousands of existing cryptocurrencies. If parties choose to make such an agreement, it is most likely that they will peg the amount of debt to the Bitcoin exchange rate. If parties choose to make such an agreement, it is most likely that they will peg the amount of debt to the Bitcoin exchange rate. In this paper, the author analyzes (crypto)currency clauses nominated in Bitcoin and their effects on contract relations in the legal system of the Republic of Serbia. This research heavy relies on the advantages of the normative and the comparative method, and various techniques of the analytical method.
With the popularity of blockchain technology, the financial security issues of blockchain transaction networks have become increasingly serious. Phishing scam detection methods will protect possible victims and build a healthier blockchain ecosystem. Usually, the existing works define phishing scam detection as a node classification task by learning the potential features of users through graph embedding methods such as random walk or graph neural network (GNN). However, these detection methods are suffered from high complexity due to the large scale of the blockchain transaction network, ignoring temporal information of the transaction. Addressing this problem, we defined the transaction pattern graphs for users and transformed the phishing scam detection into a graph classification task. To extract richer information from the input graph, we proposed a multi-channel graph classification model (MCGC) with multiple feature extraction channels for GNN. The transaction pattern graphs and MCGC are more able to detect potential phishing scammers by extracting the transaction pattern features of the target users. Extensive experiments on seven benchmark and Ethereum datasets demonstrate that the proposed MCGC can not only achieve state-of-the-art performance in the graph classification task but also achieve effective phishing scam detection based on the target users' transaction pattern graphs.
The developers of Ethereum smart contracts often implement administrating patterns, such as censoring certain users, creating or destroying balances on demand, destroying smart contracts, or injecting arbitrary code. These routines turn an ERC20 token into an administrated token - the type of Ethereum smart contract that we scrutinize in this research. We discover that many smart contracts are administrated, and the owners of these tokens carry lesser social and legal responsibilities compared to the traditional centralized actors that those tokens intend to disrupt. This entails two major problems: a) the owners of the tokens have the ability to quickly steal all the funds and disappear from the market; and b) if the private key of the owner's account is stolen, all the assets might immediately turn into the property of the attacker. We develop a pattern recognition framework based on 9 syntactic features characterizing administrated ERC20 tokens, which we use to analyze existing smart contracts deployed on Ethereum Mainnet. Our analysis of 84,062 unique Ethereum smart contracts reveals that nearly 58% of them are administrated ERC20 tokens, which accounts for almost 90% of all ERC20 tokens deployed on Ethereum. To protect users from the frivolousness of unregulated token owners without depriving the ability of these owners to properly manage their tokens, we introduce SafelyAdministrated - a library that enforces a responsible ownership and management of ERC20 tokens. The library introduces three mechanisms: deferred maintenance, board of trustees and safe pause. We implement and test SafelyAdministrated in the form of Solidity abstract contract, which is ready to be used by the next generation of safely administrated ERC20 tokens.
Abstract This article is an attempt to reconcile the requirements of the EU General Data Protection Regulation (GDPR) and anti-money laundering and combat terrorist financing (AML/CFT) instruments used in permissionless ecosystems based on distributed ledger technology (DLT). Usually, analysis is focused only on one of these regulations. Covering by this research the interplay between both regulations reveals their incoherencies in relation to permissionless DLT. The GDPR requirements force permissionless blockchain communities to use anonymization or, at the very least, strong pseudonymization technologies to ensure compliance of data processing with the GDPR. At the same time, instruments of global AML/CFT policy that are presently being implemented in many countries following the recommendations of the Financial Action Task Force, counteract the anonymity-enhanced technologies built into blockchain protocols. Solutions suggested in this article aim to induce the shaping of permissionless DLT-based networks in ways that at the same time would secure the protection of personal data according to the GDPR rules, while also addressing the money laundering and terrorist financing risks created by transactions in anonymous blockchain spaces or those with strong pseudonyms. Searching for new policy instruments is necessary to ensure that governments do not combat the development of all privacy-blockchains so as to enable a high level of privacy protection and GDPR-compliant data processing. This article indicates two AML/CFT tools which may be helpful for shaping privacy-blockchains that can enable the feasibility of such tools. The first tool is exceptional government access to transactional data written on non-transparent ledgers, obfuscated by advanced anonymization cryptography. The tool should be optional for networks as long as another effective AML/CFT measures are accessible for the intermediaries or for the government in relation to a given network. If these other measures are not available and the network does not grant exceptional access, the regulations should allow governments to combat the development of those networks. Effective tools in that scope should target the value of privacy-cryptocurrency, not its users. Such tools could include, as a tool of last resort, state attacks which would undermine the trust of the community in a specific network.
Use of distributed ledger technologies like blockchain is becoming more common in transportation/mobility ecosystems. However, cyber-security failures may occur at places where the blockchain system connects with the real world. In this paper, we propose a novel risk assessment framework for blockchain applications in smart mobility. We aim at systematically quantifying the risk by presenting ordinal values because although vulnerabilities exist in a system, it's the probability that they can be exploited and the impact of this exploitation that determine if in fact, the vulnerability corresponds to a significant risk. As a case study, we carry out an analysis in terms of quantifying the risk associated to a multi-layered Blockchain framework for Smart Mobility Data-markets (BSMD). We first construct an actor-based analysis to determine the impact of the attacks. Then, a scenario-based analysis determines the probability of occurrence of each threat. Finally, a combined analysis is developed to determine which attack outcomes have the highest risk. In the case study of the public permissioned BSMD, the outcomes of the risk analysis highlight the highest risk factors according to their impact on the victims in terms of monetary, privacy, integrity and trust. The analysis uncovers specific blockchain technology security vulnerabilities in the transportation ecosystem by exposing new attack vectors.
With the advancing technologies become tools for illicit activities and avoid detection, digital forensics is necessary for law enforcement in modern criminal investigations. In order to maintain the integrity and authenticity of the evidence, a chain of custody is essential for the successful prosecution of criminals in court. However, it is a great challenge to manage the preservation and collection of digital evidence because of its fragile and volatile in nature. Blockchain has been proposed as a promising and reliable technology to provide immutability and traceability of digital content, however, the applications of blockchain to the law enforcement agencies (LEAs) requires special attention to the security issue. In this research, we proposed a blockchain of custody framework to facilitate the security and transparency of digital evidence in criminal investigation process. The framework is implement on Ethereum smart contract to support authenticity and integrity of digital evidence in preliminary investigation, case management and court phases. We also propose the role of investigator to leverage access control in evidence creation, transferring and modification. The corresponding actions with judicial process is simulated using private ethereum blockchain. The experimental results indicate that the proposed framework can prevent digital evidence been tampered or contaminated and assure its legal defensibility with rigorous privilege management. Moreover, by successfully synchronizing digital evidence transactions to multiple nodes ensures the accountability of evidence data for every involved law enforcement agency.
Technology is revolutionizing and making positive as well as negative impacts on social animals. The social animal's behavior gets affected due to instant change in their lives. A concept of blockchain technology or distributed ledger transforms the way of their living. This technology is well known for its immutable and distributed architecture. The government focuses on such technologies rather than centralized network so that they can avoid central server banking crimes. These technologies allow social animals to stay secured and updated in an online process of information transfer. These are very famous for bitcoin, ripple, and ether transactions; however, mentioned transactions are just applications of distributed ledger. This chapter discusses the features, pros, cons, challenges, and future scope of distributed ledger. Further, it discusses the applications of blockchain technology in different sectors like identity management, smart cities, privacy protection, travel industry, electronic voting, finance, health industry, smart contracts, and hospitality.
Jan 1, 2021·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
This paper demonstrates the use of network analysis to identify core nodes associated with ransomware attacks in cryptocurrency transaction networks. The method helps trace the cyber entities involved in cryptocurrency attacks and supports intelligence efforts to identify and disrupt cryptocurrency networks. A data corpus is built by the unsupervised machine learning graph algorithm ‘DeepWalk’ [1]. DeepWalk evaluates the position of nodes within networks. It compares the relative position of different nodes (similarity) and identifies those whose removal would most affect the network (riskiness). This method helps identify on the blockchain the key nodes that are involved in the execution of a ransomware attack. When applied to the ransomware “cash out” graph, the method derived “riskiness” scores for specific nodes. Analysing the derived “riskiness” at a community level (groups of nodes in the network) provides an enhanced granularity for identifying and targeting influential nodes. Such insight could potentially support both intelligence and forensics investigations.
The aim of the article is to show cryptocurrencies as facilitators of crime, especially cybercrime. While investing in cryptocurrencies is publicly discussed, their role in the criminal world is more hidden from the public, however, causes a lot of problems for law enforcement and regulatory authorities around the world. Criminals are interested in cryptocurrencies as targets for of their attacks, means of payment and as a method of money laundering. In this article, we discuss why cryptocurrencies have become a means of payment for the criminal underworld, what benefits they have from them, and what major challenges law enforcement is facing in that regard. The survey was conducted based on reports from authorities involved in the prosecution of cybercrime. We can conclude that the organized criminal underworld has a strong interest in cryptocurrencies and their popularity among ordinary, honest citizens, as in this way it is much easier for the criminals to conceal their activities and the origin of their assets.
Elizaveta Zinovyeva, Raphael Constantin Georg Reule, Wolfgang Karl Härdle
Smart Contracts are commonly considered to be an important component or even a key to many business solutions in an immense variety of sectors and promises to securely increase their individual efficiency in an ever more digitized environment. Introduced in the early 1990's, the technology has gained a lot of attention with its application to blockchain technology to an extent, that can be considered a veritable hype. Reflecting the growing institutional interest, this intertwined exploratory study between statistics, information technology, and law contrasts these idealistic stories with the data reality and provides a mandatory step of understanding the matter, before any further relevant applications are discussed as being "factually" able to replace traditional constructions. Besides fundamental flaws and application difficulties of currently employed Smart Contracts, the technological drive and enthusiasm backing it may however serve as a jump-off board for future developments thrusting well in the presently unshakeable traditional structures.
The emergence of smart contracts has increased the attention of industry and academia to blockchain technology, which is tamper-proofing, decentralized, autonomous, and enables decentralized applications to operate in untrustworthy environments. However, these features of this technology are also easily exploited by unscrupulous individuals, a typical example of which is the Ponzi scheme in Ethereum. The negative effect of unscrupulous individuals writing Ponzi scheme-type smart contracts in Ethereum and then using these contracts to scam large amounts of money has been significant. To solve this problem, we propose a detection model for detecting Ponzi schemes in smart contracts using bytecode. In this model, our innovation is shown in two aspects: We first propose to use two bytes as one characteristic, which can quickly transform the bytecode into a high-dimensional matrix, and this matrix contains all the implied characteristics in the bytecode. Then, We innovatively transformed the Ponzi schemes detection into an anomaly detection problem. Finally, an anomaly detection algorithm is used to identify Ponzi schemes in smart contracts. Experimental results show that the proposed detection model can greatly improve the accuracy of the detection of the Ponzi scheme contracts. Moreover, the F1-score of this model can reach 0.88, which is far better than those of other traditional detection models.