Motivated by the success of Bitcoin, lots of cryptocurrencies have been created, the majority of which were implemented as smart contracts running on Ethereum and called tokens. To regulate the interaction between these tokens and users as well as third-party tools (e.g., wallets, exchange markets, etc.), several standards have been proposed for the implementation of token contracts. Although existing tokens involve lots of money, little is known whether or not their behaviors are consistent with the standards. Inconsistent behaviors can lead to user confusion and financial loss, because users/third-party tools interact with token contracts by invoking standard interfaces and listening to standard events. In this work, we take the first step to investigate such inconsistent token behaviors with regard to ERC-20, the most popular token standard. We propose a novel approach to automatically detect such inconsistency by contrasting the behaviors derived from three different sources, including the manipulations of core data structures recording the token holders and their shares, the actions indicated by standard interfaces, and the behaviors suggested by standard events. We implement our approach in a new tool named TokenScope and use it to inspect all transactions sent to the deployed tokens. We detected 3,259,001 transactions that trigger inconsistent behaviors, and these behaviors resulted from 7,472 tokens. By manually examining all (2,353) open-source tokens having inconsistent behaviors, we found that the precision of TokenScope is above 99.9%. Moreover, we revealed 11 major reasons behind the inconsistency, e.g., flawed tokens, standard methods missing, lack of standard events, etc. In particular, we discovered 50 unreported flawed tokens.
Abstract Hacks are one of the most damaging types of cryptocurrency related crime, accounting for billions of dollars in stolen funds since 2009. Professional investigators at Chainalysis have traced these stolen funds from the initial breach on an exchange to off-ramps, i.e. services where criminals are able to convert the stolen funds into fiat or other cryptocurrencies. We analyzed six hack subnetworks of bitcoin transactions known to belong to two prominent hacking groups. We analyze each hack according to eight network features, both static and temporal, and successfully classify each hack to its respective hacking group through our newly proposed method. We find that the static features, such as node balance, in degree, and out degree are not as useful in classifying the hacks into hacking groups as temporal features related to how quickly the criminals cash out. We validate our operating hypothesis that the key distinction between the two hacking groups is the acceleration with which the funds exit through terminal nodes in the subnetworks.
Cybercriminals exploit cryptocurrencies to carry out illicit activities. In this paper, we focus on Ponzi schemes that operate on Bitcoin and perform an in-depth analysis of MMM, one of the oldest and most popular Ponzi schemes. Based on 423K transactions involving 16K addresses, we show that: (1) Starting Sep 2014, the scheme goes through three phases over three years. At its peak, MMM circulated more than 150M dollars a day, after which it collapsed by the end of Jun 2016. (2) There is a high income inequality between MMM members, with the daily Gini index reaching more than 0.9. The scheme also exhibits a zero-sum investment model, in which one member's loss is another member's gain. The percentage of victims who never made any profit has grown from 0% to 41% in five months, during which the top-earning scammer has made 765K dollars in profit. (3) The scheme has a global reach with 80 different member countries but a highly-asymmetrical flow of money between them. While India and Indonesia have the largest pairwise flow in MMM, members in Indonesia have received 12x more money than they have sent to their counterparts in India.
In this explorative study we provide empirical insight into how organized crime offenders use IT to launder their money. Our empirical data consist of 30 large-scale criminal investigations into organized crime. These cases are part of the most recent, fifth data sweep of the Dutch Organized Crime Monitor (DOCM). We do not focus on cybercrime alone. Instead, we explore the financial aspects of criminal operations in a broad range of types of organized crime, i.e. from ‘traditional’ types of organized crime, such as offline drug smuggling, to cybercrime. Regarding the spending of criminal proceeds (consumption and investment), the analyses show several similarities and no major differences between traditional crime and cybercrime. When it comes to concealing criminal earnings (money laundering), we do see important differences. Financial innovation, such as the use of cryptocurrencies, seems to be limited to cases of IT-related crime. One of the most striking similarities between cybercrime and traditional crime is the offenders’ preference for cash. In the analysed cases, malware and phishing offenders as well as online drug traffickers change their digital currencies for cash, at least in part.
Ramiro Daniel Camino, Christof Ferreira Torres, Mathis Baden, Radu State
Ethereum smart contracts have recently drawn a considerable amount of attention from the media, the financial industry and academia. With the increase in popularity, malicious users found new opportunities to profit by deceiving newcomers. Consequently, attackers started luring other attackers into contracts that seem to have exploitable flaws, but that actually contain a complex hidden trap that in the end benefits the contract creator. In the blockchain community, these contracts are known as honeypots. A recent study presented a tool called HONEYBADGER that uses symbolic execution to detect honeypots by analyzing contract bytecode. In this paper, we present a data science detection approach based foremost on the contract transaction behavior. We create a partition of all the possible cases of fund movements between the contract creator, the contract, the transaction sender and other participants. To this end, we add transaction aggregated features, such as the number of transactions and the corresponding mean value and other contract features, for example compilation information and source code length. We find that all aforementioned categories of features contain useful information for the detection of honeypots. Moreover, our approach allows us to detect new, previously undetected honeypots of already known techniques. We furthermore employ our method to test the detection of unknown honeypot techniques by sequentially removing one technique from the training set. We show that our method is capable of discovering the removed honeypot techniques. Finally, we discovered two new techniques that were previously not known.
Purpose – The purpose of this paper was to conduct a systemic review of extant cryptocurrency research in order to identify important features of these studies and to provide directions for future cryptocurrency research. Methodology - The Systematic Quantitative Assessment Technique (SQAT) was used to identify and review relevant peer-reviewed journal articles that investigated various facets of cryptocurrency. \nFindings – 54 journal articles were identified from 12 high-quality databases. The findings of the review revealed that most of the studies took place in Europe, North America and Asia, while Africa has been largely ignored. The main focus of cryptocurrency articles has been on a call for regulation of cryptocurrency without much work done on how to mitigate its vulnerability to the financing of terrorism and as a tool for money laundering. Finally, most cryptocurrency articles adopted a single research method – survey. There is a need for future studies to combine a variety of methods so as to gain additional insight into the issues of cryptocurrency’s vulnerability, risk identification and mitigation, regulation and acceptability. \nResearch limitations - The use of limited but high quality academic databases means that some articles were not considered for this review. \nOriginality/value – This study is one of the few studies to conduct a systematic review on a phenomenon which has the potential to transform the global financial landscape.
Carol Alexander, Jaehyuk Choi, Heungju Park, Sungbin Sohn
Abstract BitMEX is the largest unregulated bitcoin derivatives exchange, listing contracts suitable for leverage trading and hedging. Using minute‐by‐minute data, we examine its price discovery and hedging effectiveness. We find that BitMEX derivatives lead prices on major bitcoin spot exchanges. Bid–ask spreads, interexchange spreads, and relative trading volumes are important determinants of price discovery. Further analysis shows that BitMEX derivatives have positive net spillover effects, are informationally more efficient than bitcoin spot prices, and serve as effective hedges against spot price volatility. Our evidence suggests that regulators prioritize the investigation of the legitimacy of BitMEX and its contracts.
This study unravels histories and locates meanings of specific Native and colonially imposed currencies from the 1850s to present day. Existing literature tends to reproduce colonial stereotypes of Native American peoples as technologically primitive, and has not addressed the shifts/integrations from land-based to emerging forms of digital currency. To intervene, this dissertation focuses on two case studies in which currencies–as communication technologies–are dynamic parts of much larger stories. The first case study focuses on land-based currencies–gold, coins, and beads–in the period of Oregon’s Gold Rush, specifically during the Rogue River War (1853-1856) between Native peoples and invaders/settlers. Additional chapters provide supplementary histories of related currencies and detail the political, social, and cultural shifts to digital currencies. The second case study centers on a limitedly used Indigenous cryptocurrency, or digital peer-to-peer currency, with a contested history and an explicit resistance to the U.S. dollar. Grounded in three theoretical areas, currency as communication and media, currency as entwined with nations, and de/post/settler colonialism, this dissertation works to answer a number of questions, mainly: What might the meanings embedded in land-based currency from the colonial past communicate about the present, and how does Indigenous digital currency of the present address the colonial past? Building on existing work, one finding of the first case study suggests that America’s democratic identity crisis was codified on currencies that were then used to dominate and shut out the various types of Native currencies in circulation. However, forms like shell and glass beads did not “vanish” after the Colonial Era, and remain as meaningful communicative forms that signify tribal identity present day. Findings of the second case study reveal how cryptocurrencies can be encoded with visions of tribal sovereignty, and can potentially serve tribal nations. However, they have proven problematic to implement. Further, this case study explicates the roles that racist discourses, circulated by journalistic media, play in contouring the meanings of Indigenous cryptocurrency. Native peoples have always found ways to challenge capitalism and settler colonialism. One way is through choices, re-articulation, and technological innovation around currencies.
One of the most striking financial developments of the last five years involves the emergence and rapid adoption of digital currencies, with Bitcoin being the most prominent. This paper seeks to determine whether there is evidence of collusion between mining pools (coalitions of individuals that verify transactions for monetary returns). We first constructed a theoretical framework which modeled the mining activity as an infinitely repeated game between two competing pools. By devising payoffs in the form of value functions and applying the one shot deviation principle, we found that a collusive strategy was indeed an equilibrium–if certain conditions held. However, our empirical analysis offered more ambiguous results. Ultimately, our attempt to capture peer effects suggests the relationship between a mining pool and its competitors is negative and non-linear. While this could serve as evidence against collusive behavior, we also postulate alternate explanations that could account for the finding.
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.
Using Bitcoin trading data in Venezuelan bolivars from the LocalBitcoins peer-to-peer market place and using the theory of Purchasing Power Parity (PPP), Bitcoin, as a single universal asset, is substituted for the ‘basket of goods’ normally used in the PPP, allowing the estimation of the relationship between the Venezuelan bolivar and the United States dollar. In this analysis Bitcoin is used as a tool to enable the calculation of the bolivars to dollars unofficial exchange rate and consequently the implied inflation rate. Using Bitcoin’s publicly available prices in this way enables a government’s economic mismanagement to be identified more quickly than the typical approach of measuring changes in the Consumer Price Index. Venezuela is currently in crisis, which this approach identifies as a problem as far back as 2014, as official and unofficial exchange rates diverge and inflation rates increase yearly reaching an unbelievable 70,000% in 2018 alone.
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.
Mark Weber, Giacomo Domeniconi, Jie Chen, Daniel Karl I. Weidele · 7 authors
Anti-money laundering (AML) regulations play a critical role in safeguarding\nfinancial systems, but bear high costs for institutions and drive financial\nexclusion for those on the socioeconomic and international margins. The advent\nof cryptocurrency has introduced an intriguing paradox: pseudonymity allows\ncriminals to hide in plain sight, but open data gives more power to\ninvestigators and enables the crowdsourcing of forensic analysis. Meanwhile\nadvances in learning algorithms show great promise for the AML toolkit. In this\nworkshop tutorial, we motivate the opportunity to reconcile the cause of safety\nwith that of financial inclusion. We contribute the Elliptic Data Set, a time\nseries graph of over 200K Bitcoin transactions (nodes), 234K directed payment\nflows (edges), and 166 node features, including ones based on non-public data;\nto our knowledge, this is the largest labelled transaction data set publicly\navailable in any cryptocurrency. We share results from a binary classification\ntask predicting illicit transactions using variations of Logistic Regression\n(LR), Random Forest (RF), Multilayer Perceptrons (MLP), and Graph Convolutional\nNetworks (GCN), with GCN being of special interest as an emergent new method\nfor capturing relational information. The results show the superiority of\nRandom Forest (RF), but also invite algorithmic work to combine the respective\npowers of RF and graph methods. Lastly, we consider visualization for analysis\nand explainability, which is difficult given the size and dynamism of\nreal-world transaction graphs, and we offer a simple prototype capable of\nnavigating the graph and observing model performance on illicit activity over\ntime. With this tutorial and data set, we hope to a) invite feedback in support\nof our ongoing inquiry, and b) inspire others to work on this societally\nimportant challenge.\n
This paper examines the impact of South Korea’s ban on Bitcoin futures on intraday spot volatility, liquidity and volatility–volume relationship. The results show that while reducing the permanent component of intraday spot volatility, the imposition of a ban on Bitcoin futures trading increases the transitory component. For intraday spot liquidity, different liquidity proxies indicate heterogeneous results. Moreover, we identify a positive and unidirectional effect of intraday spot volume on volatility. This effect appears to be stronger in the post-ban period. Overall, over the past few months, South Korea’s Bitcoin futures ban generally has had a significant impact on the intraday dynamics of the Bitcoin spot market.
Sushil Kumar Singh, Mikail Mohammed Salim, Minjeong Cho, Jeonghun Cha · 6 authors
Pool hopping attack is the result of miners leaving the pool when it offers fewer financial rewards and joining back when the rewards of mining yield higher rewards in blockchain networks. This act of leaving and rejoining the pool only during the good times results in the miner receiving more rewards than the computational power they contribute. Miners exiting the pool deprive it of its collective hash power, which leaves the pool unable to mine the block successfully. This results in its competitors mining the block before they can finish mining. Existing research shows pool hopping resistant measures and detection strategies; however, they do not offer any robust preventive solution to discourage miners from leaving the mining pool. To prevent pool hopping attacks, a smart contract-based pool hopping attack prevention model is proposed. The main objective of our research is maintaining the symmetrical relationship between the miners by requiring them all to continually contribute their computational power to successfully mine a block. We implement a ledger containing records of all miners, in the form of a miner certificate, which tracks the history of the miner’s earlier behavior. The certificate enables a pool manager to better initiate terms of the smart contract, which safeguards the interests of existing mining pool members. The model prevents frequent mine hoppers from pool hopping as they submit coins in the form of an escrow and risk losing them if they abandon the pool before completing mining of the block. The key critical factors that every pool hopping attack prevention solution must address and a study of comparative analysis with existing solutions are presented in the paper.
The rise of cryptocurrencies in Argentina and Venezuela in recent years shows how a highly distressed economy could become fertile ground for decentralized digital currency. This article analyzes similar traits between these two nations and examines why a collateral result of high inflation, tangled monetary regulation, and political instability could be the rapid growth of cryptocurrencies that are not linked to a central bank. Mistrust in central government authorities and national currency volatility that surpasses that of traded cryptocurrencies open a window for intangible ways of storing the falling value of local fiat currency. This article sets a general framework in order to have a better understanding of the growth of decentralized digital currencies in developing economies and continues to explain the rise of such technology in recent times in Argentina and Venezuela.
Governance issues limit blockchains' ability to evolve and face unforeseen challenges. It seems possible to argue that this impasse is because most blockchains lack meta-rules. This work considers blockchains as a socio-technical system of rules, in order to draw a comparison with legal systems. Following the comparison, one finds that most blockchains lack what, in legal theory, are considered secondary rules. That is, the meta-rule of the system.
Francisco J. Marmolejo-Cossío, Eric Brigham, Benjamin Sela, Jonathan Katz
The Bitcoin protocol prescribes certain behavior by the miners who are responsible for maintaining and extending the underlying blockchain; in particular, miners who successfully solve a puzzle, and hence can extend the chain by a block, are supposed to release that block immediately. Eyal and Sirer showed, however, that a selfish miner is incentivized to deviate from the protocol and withhold its blocks under certain conditions. The analysis by Eyal and Sirer, as well as in followup work, considers a \emph{single} deviating miner (who may control a large fraction of the hashing power in the network) interacting with a remaining pool of honest miners. Here, we extend this analysis to the case where there are \emph{multiple} (non-colluding) selfish miners. We find that with multiple strategic miners, specific deviations from honest mining by multiple strategic agents can outperform honest mining, even if individually miners would not be incentivised to be dishonest. This previous point effectively renders the Bitcoin protocol to be less secure than previously thought.
Matteo Romiti, Aljosha Judmayer, Alexei Zamyatin, Bernhard Haslhofer
Dataset retrieved and used with the code hosted here for this paper published at WEIS 2019 Abstract Miners play a key role in cryptocurrencies such as Bitcoin: they invest substantial computational resources in processing transactions and minting new currency units. It is well known that an attacker controlling more than half of the network’s mining power could manipulate the state of the system at will. While the influence of large mining pools appears evenly split, the actual distribution of mining power within these pools and their economic relationships with other actors remain undisclosed. To this end, we conduct the first in-depth analysis of mining reward distribution within three of the four largest Bitcoin mining pools and examine their cross-pool economic relationships. Our results suggest that individual miners are simultaneously operating across all three pools and that in each analyzed pool a small number of actors (≤ 20) receives over 50% of all BTC payouts. While the extent of an operator’s control over the resources of a mining pool remains an open debate, our findings are in line with previous research, pointing out centralization tendencies in large mining pools and cryptocurrencies in general
Beltrán Borja Fiz Pontiveros, Mathis Steichen, Radu State
In this work, we consider the graph of confirmed transactions in bitcoin. Understanding this graph is essential to discern the different economic activities conducted by the pseudonymous actors. In addition to traditional graph analysis methods, new metrics need to be engineered specifically for the bitcoin transaction graph. Hence, we propose a new centrality measure named mint centrality. The measure uses the inherent tree structure of transactions in bitcoin and their relation to the corresponding set of coinbase transactions, and can be evaluated with linear complexity. We present preliminary results of the mint centrality on the first 200,000 blocks of the public bitcoin blockchain.
Mining is one of the core elements of the proof-of-work based cryptocurrency economy. In this paper we investigate the generic landscape and hierarchy of miners on the example of Ethereum and Zcash, two blockchains that are among the top 5 in terms of USD value of created coins. Both chains used ASIC resistant proofs-of-work which favors GPU mining in order to keep mining decentralized. This however has changed with recent introduction of ASIC miners for these chains. This transition allows us to develop methods that might detect hidden ASIC mining in a chain (if it exists), and to study how the introduction of ASICs effects the decentralization of mining power. Finally, we describe how an attacker might use public blockchain information to invalidate the privacy of miners, deducing the mining hardware of individual miners and their mining rewards.
Cryptocurrency regulations are developing fast. Across the world, authorities are reacting to the emerging threat posed by criminals using new payment methods to conceal and launder the proceeds of their crimes. However, as the application of anti-money laundering/combating the financing of terrorism (AML/CFT) due diligence requirements becomes stricter and more entities implement preventative measures, criminals are constantly looking elsewhere for potential havens for their illicit activities. This Working Paper offers an insight into some potential consequences of changes in AML/CFT legislation in relation to cryptocurrency exchange services and virtual assets.
Christopher S. Henry, Kim P. Huynh, Gradon Nicholls
This article provides an update of the results of the 2017 Bitcoin Omnibus Survey (BTCOS) conducted by the Bank of Canada from December 12 to 15, 2017. The BTCOS was previously conducted in November and December 2016 and the results were reported in Henry, Huynh, and Nicholls (2017, forthcoming). The 2017 survey took place in an interesting time, as Bitcoin prices were increasing and reached an all-time high on December 17, 2017. During this period, the level of awareness of Bitcoin increased from 64 percent in the 2016 BTCOS to 85 percent in the 2017 BTCOS, while ownership rose from 2.9 to 5.0 percent respectively. The main reason cited by survey participants for owning Bitcoin changed from transactional purposes in 2016 to investment purposes in 2017. Further, only about half of Bitcoin owners were found to regularly use Bitcoin to buy goods or services or to send money to other people. <b>TOPICS:</b>Currency, portfolio construction, wealth management