Cybercriminals and nation-state hackers are investing heavily in strategies devised to disrupt critical infrastructure systems. Nearly one out of two Industrial Control System (ICS) computers in the energy sector had been impacted by malicious cyber activity in 2018. With threats increasing and attack vectors expanding, critical infrastructure sectors like energy need to implement innovative technology to ensure Critical Infrastructure Protection. This study reviewed blockchain research published between 2015 and 2019 in order to examine the development of blockchain, evaluate current applications of blockchain in the energy sector, and propose additional opportunities for the application of blockchain technology. Quantitative analysis revealed that blockchain-based cybersecurity research and application in the energy sector is increasing at an annual average growth rate of 169% since 2015 with intensified focus on Internet of Things (IoT) and Smart Grid infrastructures. Computed projections forecast a continued increase in the research and application of IoT and Smart Grids. Calculations indicate that nearly 50% of the new research will be in blockchain-based cybersecurity solutions such as cryptographic communications and secure email. Qualitative analysis indicates potential for blockchain- based cybersecurity solutions to provide enhanced Critical Infrastructure Protection in those sectors against pervasive phishing and social engineering threats.
Blockchain technology is one of the most exciting emerging technologies and has the capability to digitally revolutionize many systems for better security, autonomy, transparency, auditability, speed, reduced cost and efficiency. Blockchain can be regarded as a revolutionized distributed ledger technology which uses temper proof database in conjunction with consensus algorithms and cryptography. On the other hand, corruption has been a major problem in developing countries like Nigeria that bedevils their progress and development. In this paper, we investigate corrupt practices in developing countries with Nigeria as a case study. We study some blockchain use cases in some countries like Estonia and Georgia. We propose a blockchain framework to curb corrupt practices related to public funds embezzlement as the biggest corruption act. All transactions made by government agencies are stored in the blockchain shared by anti-corruption agencies, police, judiciaries and other related offices at the same time. We also propose the blockchain architecture and consensus suitable for the framework. Blockchain technology is immune to the influence of central authorities and intermediaries. It is secure against tempering and provides transparency and auditability. Hence using blockchain technology will help to tackle corrupt practices for betterment of developing countries such as Nigeria.
Despite the rapid growth in the popularity of cryptocurrency, its legal status is still unsettled. The process of issuance and circulation of the most common cryptocurrency is completely decentralized, and there is no possibility of its regulation, including from the state. Another key feature of using cryptocurrency is the anonymity of users of such cryptocurrency. These facts, as well as the possibility of uncontrolled cross-border money transfer and their subsequent cash withdrawal, are prerequisites for a high risk of the potential involvement of cryptocurrencies in criminal schemes. The article presents a brief overview of the use of cryptocurrency for criminal purposes and the need to introduce criminal law bans on criminal encroachment in the field of cryptocurrency in Russia.
Blockchain is a relatively young technology. In recent years, blockchain has gained popularity, which keeps growing. Such interest is mainly due to cryptocurrencies, such as Bitcoin and Ethereum. This technology has presented promising prospects of application. With the increasing interest in blockchain from cryptocurrency to smart contracts, there are precedents of attacks on the blockchain platform. This, in turn, encourages consideration of blockchain in terms of security, identifying vulnerabilities and predicting the emergence of new vulnerabilities. That further would allow to find new methods and solutions for blockchain security. In this paper, the known vulnerabilities were considered, as well as the known attacks on blockchain and their successful implementations in recent times.
Blockchain users are identified by addresses (public keys), which cannot be easily linked back to them without out-of-network information. This provides pseudo-anonymity, which is amplified when the user generates a new address for each transaction. Since all transaction history is visible to all users in public blockchains, finding affiliation between related addresses can hurt pseudo-anonymity. Such affiliation information can be used to discriminate against addresses that were found to be related to a specific group, or can even lead to the de-anonymization of all addresses in the associated group, if out-of-network information is available on a few addresses in that group. In this work we propose to leverage a stylometry approach on Ethereum's deployed smart contracts' bytecode and high level source code, which is publicly available by third party platforms. We explore the extent to which a deployed smart contract's source code can contribute to the affiliation of addresses. To address this, we prepare a dataset of real-world Ethereum smart contracts data, which we make publicly available; design and implement feature selection, extraction techniques, data refinement heuristics, and examine their effect on attribution accuracy. We further use these techniques to test the classification of real-world scammers data.
In recent years, illegal activities such as money laundering using cryptocurrency represented by bitcoin have been emerging. The anonymity, two-way convertibility and transnational of bitcoin are used to "launder" illegal income. Some bitcoin theft incidents are also associated with money laundering. Hackers "launder" the stolen bitcoins and eventually convert them into legal property. In this paper, we explore whether these illegal activities can be detected. First, we mine the user characteristics from the original transaction data of bitcoin. Second, the user characteristics are classified to distinguish normal users from abnormal users. Third, Gaussian Mixture Model is used to cluster users to find suspicious users. Finally, we detect the abnormal transactions among the suspicious users.
Evidence and witness play an important role to investigate crime and lawful jurisdiction in any case. But often, the victims do not get justice due to the middlemen and the altered evidences in the centralized network. Block chain is an ideal solution to ensure transparency till the highest hierarchy of jurisdiction using a decentralized peer to peer network to store data which is immutable. It is like a distributed ledger working on the proof of work algorithm that validates each amendment and modification made in a particular chain. Evichain inculcates the transparency and security of the same decentralized network in the crime investigation process. It is an application on which the entire data regarding any particular investigation is stored in a block chain with limited people having access rights. It also includes cases filed by the victims themselves. Every amendment made in the block chain is validated. Also the data access is restricted to the users with that specific private key.
Ayman Alkhalifah, Alex Ng, A. S. M. Kayes, Jabed Chowdhury · 6 authors
Blockchain technology has become one of the most popular technologies for maintaining digital transactions. From the foundation of Bitcoin to the now-predominant smart contract, blockchain technology promises to induce a shift in thought-about digital transactions in many fields, such as energy, healthcare, Internet of Things, cybersecurity, financial services, and the supply chain. Despite blockchain technology offering many cryptography advantages such as immutability, digital signature, and hashing, it has suffered from several critical cybersecurity threats and vulnerabilities. In this chapter, we build upon the previous studies on vulnerabilities and investigate over 60 real cybersecurity incidents that have been happening on the blockchain networks between 2009 and 2019. We categorize those incidents against the key cybersecurity vulnerabilities in blockchain technologies and have developed a taxonomy that captures five types of cybersecurity threats and vulnerabilities based on five main players in blockchain. The outcome of this research prompted concerns and research direction in developing countermeasures to alleviate these risks. Blockchain; Cybersecurity; Attack; Threat; Vulnerability; Taxonomy.
In July 2018, the Federal Reserve Chairman told the US Congress that cryptocurrencies are ‘great’ for money laundering. Many media headlines follow comments such as this, suggesting that cryptocurrencies are a significant criminal tool that should be feared. This article examines academic research, particularly those that analysed the Bitcoin blockchain, to see if the results matched the headlines. This was then compared to wider government and think-tank reporting. Contrary to popular opinion, this article shows that cryptocurrencies are currently used in a very small percentage of crime and they are not the great future threat that many assert. Cash is the real enemy for crime fighting and remains ‘king’. It is anonymous and far more useful to criminals than cryptocurrencies. However, the future of money is uncertain and policymakers need to understand that there is more to the debate about cryptocurrencies than the headlines suggest.
Bitcoin is a well-known cryptocurrency in which records of transactions are maintained by a P2P network to create a distributed ledger. Due to the complex nature of maintaining highly efficient, transparent and speed transactions between nodes, security is one of the primary concerns of this system. The most prominent modern-day attacks to this system are the selfish mining and double spending attacks. This survey is organized around the aspects pertaining to countermeasures of selfish mining and double spending attacks. We selected a total of 20 primary studies from recent years as a result of a systematic analysis approach. In this study we will aim to classify, analyze, and evaluate these proposed methods in order to create a secure blockchain system. These countermeasures are being developed and are being experimented with in order to mitigate and/or even eliminate these attacks from occurring. These proposed frameworks and research papers will outline the keys to improving the blockchain architecture with code scripts and design parameters to increase the functionality of the blockchain. We aim to identify implications of these countermeasures to address vulnerabilities in the blockchain network for future research on this topic.
Ankit Gangwal, Samuele Giuliano Piazzetta, Gianluca Lain, Mauro Conti
Cybercriminals have been exploiting cryptocurrencies to commit various unique financial frauds. Covert cryptomining - which is defined as an unauthorized harnessing of victims' computational resources to mine cryptocurrencies - is one of the prevalent ways nowadays used by cybercriminals to earn financial benefits. Such exploitation of resources causes financial losses to the victims. In this paper, we present our novel and efficient approach to detect covert cryptomining. Our solution is a generic solution that, unlike currently available solutions to detect covert cryptomining, is not tailored to a specific cryptocurrency or a particular form of cryptomining. In particular, we focus on the core mining algorithms and utilize Hardware Performance Counters (HPC) to create clean signatures that grasp the execution pattern of these algorithms on a processor. We built a complete implementation of our solution employing advanced machine learning techniques. We evaluated our methodology on two different processors through an exhaustive set of experiments. In our experiments, we considered all the cryptocurrencies mined by the top-10 mining pools, which collectively represent the largest share (84% during Q3 2018) of the cryptomining market. Our results show that our classifier can achieve a near-perfect classification with samples of length as low as five seconds. Due to its robust and practical design, our solution can even adapt to zero-day cryptocurrencies. Finally, we believe our solution is scalable and can be deployed to tackle the uprising problem of covert cryptomining.
Ethereum has become a widely used platform to enable secure, Blockchain-based financial and business transactions. However, a major concern in Ethereum is the security of its smart contracts. Many identified bugs and vulnerabilities in smart contracts not only present challenges to maintenance of blockchain, but also lead to serious financial loses. There is a significant need to better assist developers in checking smart contracts and ensuring their reliability.In this paper, we propose a web service tool, named SmartEmbed, which can help Solidity developers to find repetitive contract code and clone-related bugs in smart contracts. Our tool is based on code embeddings and similarity checking techniques. By comparing the similarities among the code embedding vectors for existing solidity code in the Ethereum blockchain and known bugs, we are able to efficiently identify code clones and clone-related bugs for any solidity code given by users, which can help to improve the users' confidence in the reliability of their code. In addition to the uses by individual developers, SmartEmbed can also be applied to studies of smart contracts in a large scale. When applied to more than 22K solidity contracts collected from the Ethereum blockchain, we found that the clone ratio of solidity code is close to 90\%, much higher than traditional software, and 194 clone-related bugs can be identified efficiently and accurately based on our small bug database with a precision of 96\%. SmartEmbed can be accessed at \url{http://www.smartembed.net}. A demo video of SmartEmbed is at \url{https://youtu.be/o9ylyOpYFq8}
Michael L. Spafford, Daren F. Stanaway, Sabin Chung
Purpose To analyze the CFTC’s approach to regulating cryptocurrencies and blockchain technologies in light of their cross-border nature, limitations on the CFTC’s extraterritorial authority, and the CFTC’s prerogative to work cooperatively with foreign regulators. Design/methodology/approach Discusses the principles set forth in CFTC Chairman Christopher Giancarlo’s White Paper regarding cross-border swap regulation; analyzes the similar nature of cross-border issues arising from regulation of cryptocurrencies and blockchain technologies; examines regulations and guidance implemented by foreign authorities in the blockchain and cryptocurrency space; and assesses the limitations of the CFTC’s extraterritorial authority. Findings The principles set forth in Chairman Giancarlo’s White Paper regarding cross-border swap regulation apply equally to blockchain technologies and cryptocurrencies, and as such, the CFTC may wish to pursue an analogous approach to regulating cryptocurrencies and blockchain technologies. Practical implications The CFTC should exercise deference to and cooperate with foreign counterparts to regulate cryptocurrencies and blockchain technologies that traverse international borders, thereby avoiding overlapping and potentially conflicting regulation while fostering an innovative growth environment for emerging technologies. Originality/value In-depth analysis and insight from experienced professionals in the CFTC and cross-border investigations and enforcement space.
Cryptocurrency investigations have centered almost entirely around the transfer of value “money” or a cryptocurrency asset. The use of cryptocurrency for illicit purposes, especially Bitcoin, is well documented both in academic writing, media reporting and even film documentaries. The infamous SilkRoad market place in addition to the millions of dollars spent within dark markets on drugs, guns and assassinations have grabbed the headlines. This paper looks at how blockchain is creating new areas of investigation that are yet to be explored in detail. This scenario-based research examines the hosting of stolen data (P.I.I) personal identifiable information on a distributed blockchain host where the data is also accessible. The platform used is based on Ethereum infrastructure but demonstrates just one available platform that poses the paradigm. The paper examines the considerations through the lens of an incident responder /cyber investigator, forensics examiner and data controller. The scenario highlights distinct differences in considerations from a traditional response compared to dealing with the immutable and unstoppable distributed technology. The paper concludes that more is needed to be done to understand digital forensics in the blockchain era and the need to develop beyond track and trace in the cryptocurrency investigative tool box. The discussion also brings forth how data retention and GDPR requires consideration when applying it blockchain systems.
ABSTRACT: In the last decade, a new kind of financial technology or “fintech” has emerged, bringing with it a host of legal issues. The most commonly known cryptocurrency, Bitcoin, is touted as the alternative to traditional money systems. Dozens of exchanges have emerged that can be used to store and transfer Bitcoins between virtual wallets. These exchanges are prone to being hacked, however, and without the infrastructure to back the “currency,” users have frequently lost Bitcoins to virtual thieves and been unable to recover their losses. This paper argues that class actions are an effective avenue for remedy against an exchange that has negligently lost Bitcoins. It provides a brief overview of Bitcoin’s underlying technology, the blockchain on which transactions are recorded, and the exchanges out of which they operate. Canadian class actions law is examined in the context of Bitcoin hacks to demonstrate how large-scale litigation can play an increasing role in fintech. There are many examples of cyber attack theft where class actions are the only viable remedy, given the commonality of harm, enormous aggregate losses, and lack of other recourse in an unregulated and uninsured industry. There are also inherent enforcement challenges that need to be addressed by regulators, such as jurisdiction conflict and party anonymity. New technology is constantly emerging and difficult to legally classify. Nevertheless, the paper concludes that class actions law is the best means of protecting consumer interests against fintech risks and supporting the objectives of access to justice, judicial economy, and behaviour modification.
In this paper, we introduce a machine learning predictive model that detects patterns of security vulnerabilities in smart contracts. We adapted two static code analyzers to label more than 1000 smart contracts that were verified and used on the Ethereum platform. Our model predicted a number of major software vulnerabilities with the average accuracy of 95 percent. The model currently supports smart contracts developed in Solidity, however, the approach described in this paper can be applied to other languages and blockchain platforms.
The article examines the legal status of cryptocurrencies in Russia. The authors study the civil and criminal law aspects of this phenomenon. The legislation does not define the legal status of cryptocurrencies, while the theory of law and court practice have not yet worked out a unified approach to it. The authors present an overview of the existing positions regarding this issue and suggest that cryptocurrency should be regarded as other property. It is stated that whatever position is incorporated into law, in real life cryptocurrency is in global circulation and has a great potential. As for criminal law, the authors show that it is relatively independent from civil law when dealing with issues within its object. It is suggested that, for the purposes of criminal law, the available instruments should be adjusted to enable a prompt reaction to the crimes committed at the present moment. The authors analyze the possibility of recognizing cryptocurrencies as an object and instrument of committing crimes within the framework of current legislation. Using the examples different crimes, the authors demonstrate that cryptocurrency could act as an instrument of committing them. It is also stated that cryptocurrency could be recognized as an object of some crimes. To support their position, the authors present such arguments as crimes of terrorism, illegal trade in drugs and psychoactive substances, economic crimes and some others. They also discuss cryptocurrency as an object of theft. It is proven that there is a practical necessity to recognize cryptocurrency as an object of theft. Criticism of this approach by some researchers is also discussed. The authors, however, show that it is possible to solve this problem positively. They conclude that current Russian and foreign legislation should be amended and should define the legal status of cryptocurrencies; however, the goal of criminal law could and should be achieved even before these amendments are adopted.
Recently blockchain technology has attracted increasing attention. It provides a distributed peer-to-peer network. It also allows to enlarge the contracting space using smart contracts. Smart contract is a numeric protocol which define a promises between parties. In a blockchain platform, we can find millions of smart contracts which are created by different users (developers). The smarts contracts created by users and saved in a blockchain can be similar in functionality, even if different users use different wording. This paper presents a new search engine in the blockchain. The novelty of our search engine is to help users to checks their smart contracts by referencing some similar existing smart contracts created and saved in a blockchain platform. Our search engine allows to give each user an adaptive set of similar smart-contracts based on the user's similarity needs. Our search engine is developed in the Ethereum blockchain platform. Experiments demonstrate the potential of our search engine system under different scenarios.
Blockchain technology has attracted various areas like corporations, education, government, and healthcare because of its unhackable security features. In spite of common arguments about the occurrence of Blockchain technology in terms of security and privacy, in reality, several attacks can be launched against them. This paper presents a comprehensive survey of the most vulnerable Blockchain attacks and the different approaches proposed against these attacks. This paper also provides taxonomy of attacks, which are most challengeable to Blockchain security key features. Additionally, a review of the countermeasures, which have offered solutions to avoid these attacks, has been presented.
Francesco Zola, Maria Eguimendia, Jan Lukas Bruse, Raul Orduna Urrutia
Bitcoin is a decentralized, pseudonymous cryptocurrency that is one of the most used digital assets to date. Its unregulated nature and inherent anonymity of users have led to a dramatic increase in its use for illicit activities. This calls for the development of novel methods capable of characterizing different entities in the Bitcoin network. In this paper, a method to attack Bitcoin anonymity is presented, leveraging a novel cascading machine learning approach that requires only a few features directly extracted from Bitcoin blockchain data. Cascading, used to enrich entities information with data from previous classifications, led to considerably improved multi-class classification performance with excellent values of Precision close to 1.0 for each considered class. Final models were implemented and compared using different machine learning models and showed significantly higher accuracy compared to their baseline implementation. Our approach can contribute to the development of effective tools for Bitcoin entity characterization, which may assist in uncovering illegal activities.