The first global cryptocurrency benchmarking study presents a systematic and comprehensive picture of a rapidly evolving industry, illustrating how cryptocurrencies are being used, stored, transacted and mined. The study gathered non-public data from more than 100 cryptocurrency companies and over 30 individual cryptocurrency miners in 38 countries around the world via secure web-based questionnaires, capturing an estimated 75 per cent of the cryptocurrency industry. The study breaks down the cryptocurrency industry into four key sectors – exchanges, wallets, payments and mining. Key findings and highlights from the study include our estimate that over three million unique individuals are actively using cryptocurrency today, data on regulation and compliance practices and costs at firms, and a global map of cryptocurrency mining.
Ethereum represents the second generation of blockchain technology by providing\nan open and global computing platform which allows the exchange of cryptocurrency\n(Ether) and the development of self-verifying smart contract applications.\nSmart contracts present a foundation for possessing digital assets and a variety of\ndecentralized applications within the blockchain area. Ethereum and smart contracts\nare public, distributed and immutable, as such, they are prone to vulnerabilities\nsourcing from simple coding mistakes of developers.\n\nMotivated by the security breaches and recurring financial losses in smart contracts,\nwe aim to advance the field of security in smart contract programming.\nThe main objective is to aid smart contract developers by providing a taxonomy of\nall known security issues and by inspecting the security code analysis tools used\nto identify those vulnerabilities. Based on previous research as well as attacks on\nEthereum smart contracts, we propose an updated taxonomy which categorizes\nall known vulnerabilities within their architectural and severity level. Our second\nproposed taxonomy is a novel categorization of security tools on Ethereum.\n\nFurthermore, we conduct the investigation of security code analysis tools on\nEthereum by assessing their effectiveness and accuracy. In particular, we analyze\nfour security tools, namely, Oyente, Securify, Remix, and SmartCheck. The results\nindicate that there are overall inconsistencies between the tools on different security\nproperties. SmartCheck outperformed the other tools in terms of effectiveness,\nwhereas Oyente performed the best in terms of accuracy. Furthermore, based on\nthe limitations we identified, we propose future improvements within the user interfaces,\ninterpretation of results, and additional vulnerability checks.
The gas mechanism in Ethereum charges the execution of every operation to ensure that smart contracts running in EVM (Ethereum Virtual Machine) will be eventually terminated. Failing to properly set the gas costs of EVM operations allows attackers to launch DoS attacks on Ethereum. Although Ethereum recently adjusted the gas costs of EVM operations to defend against known DoS attacks, it remains unknown whether the new setting is proper and how to configure it to defend against unknown DoS attacks. In this paper, we make the first step to address this challenging issue by first proposing an emulation-based framework to automatically measure the resource consumptions of EVM operations. The results reveal that Ethereum's new setting is still not proper. Moreover, we obtain an insight that there may always exist exploitable under-priced operations if the cost is fixed. Hence, we propose a novel gas cost mechanism, which dynamically adjusts the costs of EVM operations according to the number of executions, to thwart DoS attacks. This method punishes the operations that are executed much more frequently than before and lead to high gas costs. To make our solution flexible and secure and avoid frequent update of Ethereum client, we design a special smart contract that collaborates with the updated EVM for dynamic parameter adjustment. Experimental results demonstrate that our method can effectively thwart both known and unknown DoS attacks with flexible parameter settings. Moreover, our method only introduces negligible additional gas consumption for benign users.
Ponzi schemes are financial frauds which lure users under the promise of high\nprofits. Actually, users are repaid only with the investments of new users\njoining the scheme: consequently, a Ponzi scheme implodes soon after users stop\njoining it. Originated in the offline world 150 years ago, Ponzi schemes have\nsince then migrated to the digital world, approaching first the Web, and more\nrecently hanging over cryptocurrencies like Bitcoin. Smart contract platforms\nlike Ethereum have provided a new opportunity for scammers, who have now the\npossibility of creating "trustworthy" frauds that still make users lose money,\nbut at least are guaranteed to execute "correctly". We present a comprehensive\nsurvey of Ponzi schemes on Ethereum, analysing their behaviour and their impact\nfrom various viewpoints.\n
Conrad Burchert, Christian Decker, Roger Wattenhofer
The Bitcoin network has scalability problems. To increase its transaction rate and speed, micropayment channel networks have been proposed; however, these require to lock funds into specific channels. Moreover, the available space in the blockchain does not allow scaling to a worldwide payment system. We propose a new layer that sits in between the blockchain and the payment channels. The new layer addresses the scalability problem by enabling trustless off-blockchain channel funding. It consists of shared accounts of groups of nodes that flexibly create one-to-one channels for the payment network. The new system allows rapid changes of the allocation of funds to channels and reduces the cost of opening new channels. Instead of one blockchain transaction per channel, each user only needs one transaction to enter a group of nodes-within the group the user can create arbitrarily many channels. For a group of 20 users with 100 intra-group channels, the cost of the blockchain transactions is reduced by 90% compared to 100 regular micropayment channels opened on the blockchain. This can be increased further to 96% if Bitcoin introduces Schnorr signatures with signature aggregation.
Bitcoin as concept was coined in 2009 and can be described as a partly open and shared transactional database. What makes bitcoin unique is that for the first time, we can prove and move ownership of anything digital without a central authority. The technology facilitates many benefits, one being a worldwide, digital currency and we observe that some stores allow payments in bitcoin. Drawing on concepts from the Diffusion of Innovation theory we investigated: What are the end-users’ motivations and barriers for using bitcoin as digital currency? Through a small survey, we collected 135 answers during the summer of 2016. Our findings include that the bitcoin users embrace bitcoin due to technological curiosity, thus an individual reason. The largest group, the non-users, state that they are awaiting for others to start using bitcoin, as they question the value and security issues. We conclude that we may witness a deadlock where “everybody waits for everybody”, and that more research is needed.
On-line commercial transactions involve an inherent mistrust between participant parties since, sometimes, no previous relation exists between them. Such mistrust may be a deadlock point in a trade transaction where the buyer does not want to perform the payment until the seller sends the goods and the seller does not want to do so until the buyer pays for the purchase. In this paper we present a fair protocol for data trading where the commercial deal, in terms of delivering the data and performing the payment, is atomic, since the seller cannot redeem the payment unless the buyer obtains the data and the buyer cannot obtain the data without performing the payment. The protocol is based on Bitcoin scripting language and the fairness of the protocol can be probabilistically enforced.
Olivier Scaillet, Adrien Treccani, Christopher Trevisan
We use the database leak of Mt. Gox exchange to analyze the dynamics of the price of bitcoin from June 2011 to November 2013. This gives us a rare opportunity to study an emerging retail-focused, highly speculative and unregulated market with trader identifiers at a tick transaction level. Jumps are frequent events and they cluster in time. The order flow imbalance and the preponderance of aggressive traders, as well as a widening of the bid-ask spread predict them. Jumps have short-term positive impact on market activity and illiquidity and induce a persistent change in the price.
Bitcoin has the largest share in the total capitalization of cryptocurrency markets currently reaching above 70 billion USD. In this work we focus on the price of Bitcoin in terms of standard currencies and their volatility over the last five years. The average day-to-day return throughout this period is 0.328%, amounting in exponential growth from 6 USD to over 4,000 USD per 1 BTC at present. Multi-scale analysis is performed from the level of the tick data, through the 5 min, 1 hour and 1 day scales. Distribution of trading volumes (1 sec, 1 min, 1 hour and 1 day) aggregated from the Kraken BTCEUR tick data is provided that shows the artifacts of algorithmic trading (selling transactions with volume peaks distributed at integer multiples of BTC unit). Arbitrage opportunities are studied using the EUR, USD and CNY currencies. Whereas the arbitrage spread for EUR-USD currency pair is found narrow at the order of a percent, at the 1 hour sampling period the arbitrage spread for USD-CNY (and similarly EUR-CNY) is found to be more substantial, reaching as high as above 5 percent on rare occasions. The volatility of BTC exchange rates is modeled using the day-to-day distribution of logarithmic return, and the Realized Volatility, sum of the squared logarithmic returns on 5-minute basis. In this work we demonstrate that the Heterogeneous Autoregressive model for Realized Volatility Andersen et al. (2007) applies reasonably well to the BTCUSD dataset. Finally, a feed-forward neural network with 2 hidden layers using 10-day moving window sampling daily return predictors is applied to estimate the next-day logarithmic return. The results show that such an artificial neural network prediction is capable of approximate capture of the actual log return distribution; more sophisticated methods, such as recurrent neural networks and LSTM (Long Short Term Memory) techniques from deep learning may be necessary for higher prediction accuracy.
Luuc Van Der Horst, Kim‐Kwang Raymond Choo, Nhien‐An Le‐Khac
Bitcoin cryptocurrency is reportedly one widely used digital currency in criminal activities (e.g. used for online purchases of illicit drugs and paying of ransom in ransomware cases). However, there has been limited forensic research of bitcoin clients in the literature. In this paper, the process memory of two popular bitcoin clients, bitcoin Core and electrum, is examined with the aims of identifying potential sources and types of potential relevant data (e.g. bitcoin keys, transaction data and passphrases). Artefacts obtained from the process memory are also studied with other artefacts obtained from the client device (application files on disk and memory-mapped files and registry keys). Findings from this study suggest that both bitcoin Core and electrum's process memory is a valuable source of evidence, and many of the artefacts found in process memory are also available from the application and wallet files on the client device (disk).
The Bitcoin protocol allows to save arbitrary data on the blockchain through a special instruction of the scripting language, called OP_RETURN. A growing number of protocols exploit this feature to extend the range of applications of the Bitcoin blockchain beyond transfer of currency. A point of debate in the Bitcoin community is whether loading data through OP_RETURN can negatively affect the performance of the Bitcoin network with respect to its primary goal. This paper is an empirical study of the usage of OP_RETURN over the years. We identify several protocols based on OP_RETURN, which we classify by their application domain. We measure the evolution in time of the usage of each protocol, the distribution of OP_RETURN transactions by application domain, and their space consumption.
The meteoric rise of Bitcoin has led to heightened investment, academic, commercial, numismatic, transactional, and practitioner interest in that cryptocurrency, as well as in the growing array of such instruments worldwide. This leads to an accentuated need for an examination of the historical evolution of Bitcoin as the seminal instrument in the development of cryptocurrencies, and this discussion paper seeks to address that gap.
Christian Badertscher, Ueli Maurer, Daniel Tschudi, Vassilis Zikas
Abstract Bitcoin is one of the most prominent examples of a distributed cryptographic protocol that is extensively used in reality. Nonetheless, existing security proofs are property-based, and as such they do not support composition. In this work, we put forth a universally composable treatment of the Bitcoin protocol. We specify the goal that Bitcoin aims to achieve as an instance of a parameterizable ledger functionality and present a UC abstraction of the Bitcoin blockchain protocol. Our ideal functionality is weaker than the first proposed candidate by Kiayias, Zhou, and Zikas [EUROCRYPT’16], but unlike the latter suggestion, which is arguably not implementable by the UC Bitcoin protocol, we prove that the one proposed here is securely UC-realized by the protocol assuming access to a global clock, to model time-based executions, a random oracle, to model hash functions, and an idealized network, to model message dissemination. We further show how known property-based approaches can be cast as special instances of our treatment and how their underlying assumptions can be cast in UC as part of the setup functionalities and without restricting the environment or the adversary.
Abstract Bitcoin provides its users with transaction-processing services which are similar to those of traditional payment systems. This article models the novel economic structure implied by Bitcoin’s innovative decentralized design, which allows the payment system to be reliably operated by unrelated parties called miners. We find that this decentralized design protects users from monopoly pricing. Competition among service providers within the platform and free entry imply no entity can profitably affect the level of fees paid by users. Instead, a market for transaction-processing determines the fees users pay to gain priority and avoid transaction-processing delays. The article (i) derives closed-form formulas of the fees and waiting times and studies their properties, (ii) compares pricing under the Bitcoin Payment System to that under a traditional payment system operated by a profit-maximizing firm, and (iii) suggests protocol design modifications to enhance the platform’s efficiency. The Appendix describes and explains the main attributes of Bitcoin and the underlying blockchain technology.
Investor and media attention in Bitcoin has increased substantially in recently years, reflected by the incredible surge in news articles and considerable rise in the price of Bitcoin. Given the increased attention, there little is known about the behaviour of Bitcoin prices and therefore we add to the literature by studying price clustering. We find significant evidence of clustering at round numbers, with over 10% of prices ending with 00 decimals compared to other variations but there is no significant pattern of returns after the round number. We also support the negotiation hypothesis of Harris (1991) by showing that price and volume have a significant positive relationship with price clustering at whole numbers.
The internet of things (IoT) enabled a common operating picture (COP) across the various applications of modern day living. The COP is achieved through the advancements seen in wireless sensor network devices that were able to communicate through the network thereby exchanging information and performing various analysis. In IoT, the exchange of information and data authentication is only done through the central server there by leading to the security and privacy concerns. Chances of device spoofing, false authentication, less reliability in data sharing could happen. To address such security and privacy concerns, a central server concept is eliminated and blockchain (BC) technology is introduced as a part of IoT. This paper elaborates the possible security and privacy issues considering the component interaction in IoT and studies how the distributed ledger based blockchain (DLBC) technology contribute to it. Applications of BC with respect to focused sectors and category were clearly studied here. Various challenges specific to IoT and IoT with BC were also discussed to understand blockchain technology contribution.