The issue of market efficiency for cryptocurrency exchanges has been largely unexplored. Here we put Bitcoin, the leading cryptocurrency, on a test by studying the applicability of the Efficient Market Hypothesis by Fama from two viewpoints: (1) the existence of profitable arbitrage spread among Bitcoin exchanges, and (2) the possibility to predict Bitcoin prices in EUR (time period 2013-2017) and the direction of price movement (up or down) on the daily trading scale. Our results show that the Bitcoin market in the time period studied is partially inefficient. Thus the market process is predictable to a degree, hence not a pure martingale. In particular, the F-measure for XBTEUR time series obtained by three major recurrent neural network based machine learning methods was about 67%, i.e. a way above the unbiased coin tossing odds of 50% equal chance.
The Bitcoin protocol is a significant milestone in the history of money. However, its adoption is currently constrained by the transaction limits of the system. As the chief problem of blockchain technology, the scaling issue has attracted many valuable solutions both on-chain and off-chain. In this paper, our goal is to explore the notion of unspent transaction outputs (UTXOs) to propose an augmented Bitcoin protocol that can scale gracefully. Our proposal aims to increase the transaction throughput by partitioning the UTXO space and splitting the blockchain. In addition, a new type of Bitcoin node is introduced to preserve the capability to run validating nodes in low-bandwidth environments, despite the increased transaction throughput.
Sep 22, 2018·2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation
Bitcoin, as a decentralized digital currency, has caused extensive research interest. There are many studies based on related protocols on Bitcoin, Bitcoin-based voting protocols also received attention in related literature. In this paper, we propose a Bitcoin-based decentralized privacy-preserving voting mechanism. It is assumed that there are n voters and m candidates. The candidate who obtains t ballots can get x Bitcoins from each voter, namely nx Bitcoins in total. We use a shuffling mechanism to protect voter's voting privacy, at the same time, decentralized threshold signatures were used to guarantee security and assign voting rights. The protocol can achieve correctness, decentralization and privacy-preservings. By contrast with other schemes, our protocol has a smaller number of transactions and can achieve a more functional voting method.
Elena Kirillova, Albert Valentinovich Pavlyuk, I. A. Mikhaylova, Зульфугарзаде Теймур Эльдарович · 5 authors
The current article examines the peculiarities and legal nature of Bitcoin, Lifecoin, Namecoin, Quark, WebMoney, Ripple and other virtual currencies. There is no single understanding of the legal essence of virtual currency in the world today; therefore, the legal status of such currencies is not officially fixed and there are no official rates of Bitcoins or other crypto currencies against national currencies. Their rate is determined in the course of trading at virtual Bitcoin exchanges and exchange platforms. Such a situation is dictated by the novelty of legal relations in the field of crypto currency circulation, the risks of their implementation, as well as security problems. The main goal of the study is to define the legal nature and features of virtual currencies and the possibilities of legislative regulation of using crypto currencies. When writing the article, the methods of collecting and studying singularities have been used, as well as generalization methods, the methods of scientific abstraction, and the methods of studying regularities. The study has concluded that it is advisable to provide for the licensing of mining and crypto trading at the international level, customers should be identified when selling and buying virtual currencies, introducing a special verification procedure for Bitcoin users will prevent the abuse of virtual currencies for money laundering and terrorism financing. As a result of the analysis, a definition has been given, and the main features and functions of the virtual currency have been highlighted. It has been proved that virtual currencies are a new kind of electronic money stored in computer memory, the monetary value of the virtual currency is managed by means of a technical device. Virtual currency is a new means of payment and does not require access to deposit accounts.
The bitcoin price has surged in recent years and it has also exhibited phases of rapid decay. In this paper we address the question to what extent this novel cryptocurrency market can be viewed as a classic or semi-efficient market. Novel and robust tools for estimation of multi-fractal properties are used to show that the bitcoin price exhibits a very interesting multi-scale correlation structure. This structure can be described by a power-law behavior of the variances of the returns as functions of time increments and it can be characterized by two parameters, the volatility and the Hurst exponent. These power-law parameters, however, vary in time. A new notion of generalized Hurst exponent is introduced which allows us to check if the multi-fractal character of the underlying signal is well captured. It is moreover shown how the monitoring of the power-law parameters can be used to identify regime shifts for the bitcoin price. A novel technique for identifying the regimes switches based on a goodness of fit of the local power-law parameters is presented. It automatically detects dates associated with some known events in the bitcoin market place. A very surprising result is moreover that, despite the wild ride of the bitcoin price in recent years and its multi-fractal and non-stationary character, this price has both local power-law behaviors and a very orderly correlation structure when it is observed on its entire period of existence.
We study the probabilistic distribution of the confirmation time of Bitcoin transactions, conditional on the current memory pool (i.e., the queue of transactions awaiting confirmation). The results of this paper are particularly interesting for users that want to make a Bitcoin transaction during `heavy-traffic situations', when the transaction demand exceeds the block capacity. In such situations, Bitcoin users tend to bid up the transaction fees, in order to gain priority over other users that pay a lower fee. We argue that the time until a Bitcoin transaction is confirmed can be modelled as a particular stochastic fluid queueing process (to be precise: a Cramér-Lundberg process). We approximate the queueing process in two different ways. The first approach leads to a lower bound on the confirmation probability, which becomes increasingly tight as traffic decreases. The second approach relies on a diffusion approximation with a continuity correction, which becomes increasingly accurate as traffic intensifies. The accuracy of the approximations under different traffic loads are evaluated in a simulation study.
The Bitcoin protocol prevents the occurrence of double-spending (DS), i.e. the utilization of the same currency unit more than once. At the same time a DS attack, where more conflicting transactions are generated, might be performed to defraud a user, e.g. a merchant. Therefore, in this work, we propose a model for detecting the presence of conflicting transactions by means of an 'oracle' that polls a subset of nodes of the Bitcoin network. We assume that the latter has a complex structure. So, we investigate the relation between the topology of several complex networks and the optimal amount, and distribution, of a subset of nodes chosen by the oracle for polling. Results show that small-world networks require to poll a smaller amount of nodes than regular networks. In addition, in random topologies, a small number of polled nodes can make a detection system fast and reliable even if the underlying network grows.
Nino Antulov-Fantulin, Dijana Tolić, Matija Piškorec, Ce Zhang · 5 authors
In this paper, we study the possibility of inferring early warning indicators (EWIs) for periods of extreme bitcoin price volatility using features obtained from Bitcoin daily transaction graphs. We infer the low-dimensional representations of transaction graphs in the time period from 2012 to 2017 using Bitcoin blockchain, and demonstrate how these representations can be used to predict extreme price volatility events. Our EWI, which is obtained with a non-negative decomposition, contains more predictive information than those obtained with singular value decomposition or scalar value of the total Bitcoin transaction volume.
Nany Salwa, Nidya Tatsara, Ridha Amalia, Aja Fatimah Zohra
ABSTRAK. Bitcoin merupakan mata uang virtual yang saat ini banyak diminati sebagai alternatif investasi. Metode ARIMA adalah salah satu metode yang digunakan untuk peramalan data deret waktu. Tujuan dari penelitian ini adalah untuk membuat model dan meramalkan harga bitcoin. Data yang digunakan adalah data sekunder yaitu berupa data harga bitcoin selama 60 periode mulai dari tanggal 10 Januari 2018 sampai dengan 10 Maret 2018 untuk memprediksikan harga bitcoinselama 30 periode kedepan mulai tanggal 11 Maret 2018 sampai dengan 09 April 2018. Dari hasil penelitian menunjukkan bahwa data harga bitcoin selama 60 periode tidak memenuhi asumsi stasioneritas terhadap rata-rata untuk itu dilakukan proses differencing tingkat 2 agar data menjadi stasioner. Model ARIMA yang dihasilkan adalah ARIMA(0,2,1) yaitu Zt = μ - 0,9647Zt-1 + at dan model tersebut cocok digunakan untuk peramalan data harga bitcoin. Hasil peramalan dengan menggunakan model ARIMA(0,2,1) menunjukkan bahwa harga bitcoin untuk 30 periode kedepannya mengalami penurunan secara perlahan dan hasil peramalan mendekati data sebenarnya. ABSTRACT. Bitcoin is a virtual currency that is currently much interested as an alternative investment. ARIMA method is one of the methods used for forecasting time series data. The purpose of this research is to create a model and predicted the price of the bitcoin. The data used are secondary data that is in the form of price bitcoin during 60 periods starting from January 10, 2018 up to 10 March 2018 to predict price bitcoin for 30 the next periods began March 11 and ended on 9 April 2018 2018. Based on the results of the study showed that the price of bitcoin during 60 periods did not fullfiled the assumptions of stasioneritas towards the mean. Therefore using the differencing level 2 process, so the data becomes stationary. The result of ARIMA model is ARIMA(0, 2, 1) Zt = μ - 0,9647Zt-1 + at and the model fits the data used for forecasting price bitcoin. The results of the forecasting model using ARIMA (0, 2, 1) shows that the price of the bitcoin for 30 periods has decreased gradually and forecasting results close to the actual data.
Selfish mining, which is an attack on the integrity of the Bitcoin network, was first proposed by Cornell researchers Emin Gun Sirer and Ittay Eyal in 2013. Selfish mining attack also exists in most Nakamoto consensus protocols. Generally speaking, selfish mining strategy can comprise a Nakamoto consensus system with less than 25% mining power of the whole system. We have discussed how the Bicomp can resist selfish mining in our former paper "Bicomp: A Bilayer Scalable Nakamoto Consensus Protocol". In this technical report, we give a detailed derivation on the conditions a selfish attacker should meet to earn more revenues through selfish mining. And we also get a conclusion that through adjusting macroblock difficulties together with tenure lengths, the Bicomp protocol has high resistant towards selfish mining.
Yazan Boshmaf, Husam Al Jawaheri, Mashael Al Sabah
Annotating blockchains with auxiliary data is useful for many applications. For example, e-crime investigations of illegal Tor hidden services, such as Silk Road, often involve linking Bitcoin addresses, from which money is sent or received, to user accounts and related online activities. We present BlockTag, an open-source tagging system for blockchains that facilitates such tasks. We describe BlockTag's design and present three analyses that illustrate its capabilities in the context of privacy research and law enforcement.
Airdrops are a popular method of distributing cryptocurrencies and tokens. While often considered risk-free from the point of view of recipients, their impact on privacy is easily overlooked. We examine the Clam airdrop of 2014, a forerunner to many of today's airdrops, that distributed a new cryptocurrency to every address with a non-dust balance on the Bitcoin, Litecoin and Dogecoin blockchains. Specifically, we use address clustering to try to construct the one-to-many mappings from entities to addresses on the blockchains, individually and in combination. We show that the sharing of addresses between the blockchains is a privacy risk. We identify instances where an entity has disclosed information about their address ownership on the Bitcoin, Litecoin and Dogecoin blockchains, exclusively via their activity on the Clam blockchain.
German Abstract: Your legal concepts of property, expression, identity, movement, and context do not apply to us. They are all based on matter, and there is no matter here.“ Dies proklamierte einst der amerikanische Poet und Freigeist John Perry Barlow, der als Mitbegrunder der NGO Electronic Frontier Foundation fur Rechte im digitalen Zeitalter und eine moglichst weitgehende Deregulierung des Internets eintrat. Digitale Phanomene wie Kryptowahrungen sind nur schwer den bestehenden Konzepten einer ursprunglich durch korperliche Gegenstande gepragten Rechtsordnung zu unterwerfen. Dieser Aufsatz versucht am Beispiel von Bitcoins diese Erscheinungen in bestehende zivilrechtliche Strukturen einzuordnen und zu klaren, ob der Gesetzgeber regulierend einschreiten sollte. Hierzu werden nach einer Einleitung zu Kryptowahrungen (I.) ihre Rechtsnatur (II.) und Behandlung i.R.d. Schuldrechts (III.) erortert.
English Abstract: Your legal concepts of property, expression, identity, movement, and context do not apply to us. They are all based on matter, and there is no matter here. This was once proclaimed by the American poet and freethinker John Perry Barlow, who as co-founder of the NGO Electronic Frontier Foundation advocated rights in the digital age and the deregulation of the internet as far as possible. Digital phenomena such as cryptocurrencies are difficult to subordinate to existing concepts of a legal system originally shaped by physical objects. Using Bitcoins as an example, this article attempts to integrate these phenomena into existing civil law structures and to clarify whether the legislator should intervene to regulate them. After an introduction to cryptocurrencies (I.) their legal nature (II.) and treatment in the law of obligations (III.) are discussed.
We initiate the study of quantum races, games where two or more quantum computers compete to solve a computational problem. While the problem of dueling algorithms has been studied for classical deterministic algorithms, the quantum case presents additional sources of uncertainty for the players. The foremost among these is that players do not know if they have solved the problem until they measure their quantum state. This question of `when to measure?' presents a very interesting strategic problem. We develop a game-theoretic model of a multiplayer quantum race, and find an approximate Nash equilibrium where all players play the same strategy. In the two-party case, we further show that this strategy is nearly optimal in terms of payoff among all symmetric Nash equilibria. A key role in our analysis of quantum races is played by a more tractable version of the game where there is no payout on a tie; for such races we completely characterize the Nash equilibria in the two-party case. One application of our results is to the stability of the Bitcoin protocol when mining is done by quantum computers. Bitcoin mining is a race to solve a computational search problem, with the winner gaining the right to create a new block. Our results inform the strategies that eventual quantum miners should use, and also indicate that the collision probability---the probability that two miners find a new block at the same time---would not be too high in the case of quantum miners. Such collisions are undesirable as they lead to forking of the Bitcoin blockchain.
This article deals with the concepts of social currencies and cryptocurrencies. The objective of the present paper is to identify similarities and differences between to two currency systems which represent a new generation of money that exists alongside the official and legal money system. The paper includes an analysis of the major characteristics of both currencies, their operating mechanisms in global and local contexts, as well as their risks and challenges for the financial markets. The article uses a mainly documentary research method and presents selected contributions of experts on the topics of social currencies and cryptocurrencies. Furthermore, empirical evidence is presented to highlight some important characteristics of the Bitcoin currency. The principal result of the paper is that, indeed there exist similarities between social currencies and cryptocurrencies, as for example the absence of a central bank, a lack of regulation and a limited minting process. However, because of aspects like their different origins, their local vs. global character and their inherent financial risks, the two money systems need to be interpreted as fundamentally different. Especially with reference to globally operating cryptocurrencies, given that there does not exist any public cover of the currency nor sufficient regulation, risk management mechanisms need to be improved in order to diminish the speculative tendencies inherent to this currency.
In this work, we propose an order book model with herd behavior. The proposed model is built upon two distinct approaches: a recent empirical study of the detailed order book records by Kanazawa et al. [Phys. Rev. Lett. 120, 138301] and financial herd behavior model. Combining these approaches allows us to propose a model that replicates the long-range memory of absolute returns and trading activity. We compare the statistical properties of the model against the empirical statistical properties of the Bitcoin exchange rates and New York stock exchange tickers. We also show that the fracture in the spectral density of the high-frequency absolute return time series might be related to the mechanism of convergence towards the equilibrium price.
Blockchain's vast applications in different industries have drawn several researchers to pursue extensive research in securing blockchain technologies. In recent times we could see several institutions coming together to create consortium based blockchain networks such as Hyperledger. Although for applications of blockchain such as Bitcoin, Litcoin, etc. the majority-attack might not be a great threat but for consortium based blockchain networks where we could see several institutions such as public, private, government, etc. are collaborating, the majority-attack might just prove to be a prevalent threat if collusion among these institutions takes place. This paper proposes a methodology where we can use intelligent software agents to monitor the activity of stakeholders in the blockchain networks to detect anomaly such as collusion, using supervised machine learning algorithm and algorithmic game theory and stop the majority attack from taking place.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Reza M. Parizi, Ali Dehghantanha, Kim‐Kwang Raymond Choo, Amritraj Singh
The emerging blockchain technology supports decentralized computing paradigm shift and is a rapidly approaching phenomenon. While blockchain is thought primarily as the basis of Bitcoin, its application has grown far beyond cryptocurrencies due to the introduction of smart contracts. Smart contracts are self-enforcing pieces of software, which reside and run over a hosting blockchain. Using blockchain-based smart contracts for secure and transparent management to govern interactions (authentication, connection, and transaction) in Internet-enabled environments, mostly IoT, is a niche area of research and practice. However, writing trustworthy and safe smart contracts can be tremendously challenging because of the complicated semantics of underlying domain-specific languages and its testability. There have been high-profile incidents that indicate blockchain smart contracts could contain various code-security vulnerabilities, instigating financial harms. When it involves security of smart contracts, developers embracing the ability to write the contracts should be capable of testing their code, for diagnosing security vulnerabilities, before deploying them to the immutable environments on blockchains. However, there are only a handful of security testing tools for smart contracts. This implies that the existing research on automatic smart contracts security testing is not adequate and remains in a very stage of infancy. With a specific goal to more readily realize the application of blockchain smart contracts in security and privacy, we should first understand their vulnerabilities before widespread implementation. Accordingly, the goal of this paper is to carry out a far-reaching experimental assessment of current static smart contracts security testing tools, for the most widely used blockchain, the Ethereum and its domain-specific programming language, Solidity to provide the first...
Blockchain has received great attention in recent years and motivated innovations in different scenarios. However, many vital issues which affect its performance are still open. For example, it is widely convinced that high level of security and scalability and full decentralization are still impossible to achieve simultaneously. In this paper, we propose Bicomp, a bilayer scalable Nakamoto consensus protocol, which is an approach based on high security and pure decentralized Nakamoto consensus, and with a significant improvement on scalability. In Bicomp, two kinds of blocks are generated, i.e., microblocks for concurrent transaction packaging in network, and macroblocks for leadership competition and chain formation. A leader is elected at beginning of each round by using a macroblock header from proof-of-work. An elected leader then receives and packages multiple microblocks mined by different nodes into one macroblock during its tenure, which results in a bilayer block structure. Such design limits a leader's power and encourages as many nodes as possible to participate in the process of packaging transactions, which promotes the sharding nature of the system. Furthermore, several mechanisms are carefully designed to reduce transaction overlapping and further limit a leader's power, among which a novel transaction diversity based metric is proposed as the second level criteria besides the longest-chain-first principle on selecting a legitimate chain when fork happens. Security issues and potential attacks to Bicomp are extensively discussed and experiments for evaluation are performed. From the experimental results based on 50 nodes all over the world, Bicomp achieves significant improvement on scalability than that of Bitcoin and Ethereum, while the security and decentralization merits are still preserved.
Marco Conoscenti, Antonio Vetrò, Juan Carlos De Martin, Federico Spini
The Lightning Network (LN) is one of the most promising off-chain scaling solutions for Bitcoin, as it enables off-chain payments which are not subject to the well-known blockchain scalability limit. In this work, we introduce CLoTH, a simulator for HTLC payment networks (of which LN is the best working example). It simulates input-defined payments on an input-defined HTLC network and produces performance measures in terms of payment-related statistics (such as time to complete payments and probability of payment failure). CLoTH helps to predict issues and obstacles that might emerge in the development stages of an HTLC payment network and to estimate the effects of an optimisation action before deploying it. We conducted simulations on a recent snapshot of the HTLC payment network of LN. These simulations allowed us to identify network and payments configurations for which a payment is more likely to fail than to succeed. We proposed viable solutions to avoid such configurations.
Blockchain is based on a P2P network, supporting decentralized consensus of current cryptocurrencies. Since bitcoin and altcoins all utilize an underlying blockchain, they are therefore greatly affected by the performance of the P2P network. In bitcoin, the miners are engaged in a time-sensitive competition to solve a Proof-of-Work problem to extend the blockchain. This consequently raises a critical problem to minimize the time between the propagation of a winning block and the beginning of the next round of the competition. This paper proposes a method that selects a node's closest neighbors to make messages propagate in the whole network in time. The method measures the distance from a node to its neighbor using transmission latency; thus, the lower the latency, the closer the neighbor. Simulations showed a good rate of decrease in average propagation latency and maximum propagation latency, compared to the classic method. Furthermore, this paper not only proposes the principle of establishing connections based on latency, but also evaluates the influence of the number of simultaneously established connections.
Marian Gidea, Daniel Goldsmith, Yuri A. Katz, Pablo Roldan · 5 authors
We analyze the time series of four major cryptocurrencies (Bitcoin, Ethereum,\nLitecoin, and Ripple) before the digital market crash at the end of 2017 -\nbeginning 2018. We introduce a methodology that combines topological data\nanalysis with a machine learning technique -- $k$-means clustering -- in order\nto automatically recognize the emerging chaotic regime in a complex system\napproaching a critical transition. We first test our methodology on the complex\nsystem dynamics of a Lorenz-type attractor, and then we apply it to the four\nmajor cryptocurrencies. We find early warning signals for critical transitions\nin the cryptocurrency markets, even though the relevant time series exhibit a\nhighly erratic behavior.\n
Money is one of the powerful institutions that humankind created and developed and nowadays it affects all of aspects of social human life. Money essentially is production of human socialization and we should think of it as a social reality that although has a special and independent role for each individual, but it has overall acceptance in the society. Bitcoin is a decentralized electronic fiat currency implemented using cryptography and peer-to-peer technology. Because of increasing development of bitcoin and also other similar currencies, our monetary policy-makers should take proper position about it. In this study we make an analysis about value of bitcoin in context of Etebariat theory developed by Allameh Tabataba’i and argue that value of bitcoin is consistent with this context. Our study about monetary and banking schools like metalism, chartalism, money in circle and banking shows that because of peer-to-peer system of Bitcoin, although Bitcoin is inconsistent with all of the abovementioned theories, but it is consist with Etebariat theory because of no need to third party. So Bitcoin is a counter-example to classical theory of money and it verify Etebariat theory.