The purpose of this paper is to examine in what ways capital-B Bitcoin, the system, and lower-b bitcoin, the unit of account, are or are not money. Bitcoin is the largest, by market capitalization, financial asset labeled "cryptocurrency" and the first decentralized digital currency. The paper canvasses the academic, business and technical literature to scrutinize the validity of this neologism's implied equivalency to money as a concept, system and artifact from historical, economic, political, teleological, theoretical and functional perspectives. The author(s) of Bitcoin invented blockchain, that is a shared, decentralized, time stamped, public ledger, to solve the problem of double spending. The risk of fraud, paying several counterparties with the same coin, was an intractable limitation on digital cash replacing paper money. The addition of blockchain to "proof of work" and advanced cryptography was a major advance in electronic cash systems. The combination of other features with this innovation, in particular a programmed steady growth and overall limit on supply, created in Bitcoin and other cryptocurrencies that followed a potential challenger to fiat currencies. This paper tests Bitcoin's progress and prospects in credibly replacing sovereign currencies in theory and in practice. Our conclusion is that the replacement of fiat currencies by cryptocurrencies in the world economy is not imminent. However, the underlying technology of cryptocurrencies holds great promise for improving the security and efficiency of the global financial and monetary systems.
Nowadays, blockchain is becoming a synonym for distributed ledger technology. However, blockchain is only one of the specializations in the field and is currently well-covered in existing literature, but mostly from a cryptographic point of view. Besides blockchain technology, a new paradigm is gaining momentum: directed acyclic graphs. The contribution presented in this paper is twofold. Firstly, the paper analyzes distributed ledger technology with an emphasis on the features relevant to distributed systems. Secondly, the paper analyses the usage of directed acyclic graph paradigm in the context of distributed ledgers, and compares it with the blockchain-based solutions. The two paradigms are compared using representative implementations: Bitcoin, Ethereum and Nano. We examine representative solutions in terms of the applied data structures for maintaining the ledger, consensus mechanisms, transaction confirmation confidence, ledger size, and scalability.
Hadeka Rasul is a recent graduate of Seton Hall University, where she studied Political Science and Economics. She is currently a Business Analyst at Birchbox. As a part of Pi Sigma Alpha, she serves on the executive board of the chapter and is an executive editor for the Political Science journal. She expects to attend graduate school to attain an MBA in the future.
Nowadays, blockchain is becoming a synonym for distributed ledger technology.\nHowever, blockchain is only one of the specializations in the field and is\ncurrently well-covered in existing literature, but mostly from a cryptographic\npoint of view. Besides blockchain technology, a new paradigm is gaining\nmomentum: directed acyclic graphs. The contribution presented in this paper is\ntwofold. Firstly, the paper analyzes distributed ledger technology with an\nemphasis on the features relevant to distributed systems. Secondly, the paper\nanalyses the usage of directed acyclic graph paradigm in the context of\ndistributed ledgers, and compares it with the blockchain-based solutions. The\ntwo paradigms are compared using representative implementations: Bitcoin,\nEthereum and Nano. We examine representative solutions in terms of the applied\ndata structures for maintaining the ledger, consensus mechanisms, transaction\nconfirmation confidence, ledger size, and scalability.\n
Bitcoin, the most prominent and first unregulated Cryptocurrency, has been the focal point of much international spotlight and controversy in the recent years. Due to its unregulated nature, technical requirements, and unknown potential and value, there has been much debate about what to classify Bitcoin as. Along with this, Bitcoin has been extremely inefficient throughout its lifetime, and nobody truly knows how to monitor or predict possible future values. The purpose of this project was to try and get a deeper understanding of the microstructure of Bitcoin, and what microstructures impact its value.
Cryptocurrency wallets store the wallet's private key(s), and hence, are a lucrative target for attackers. With possession of the private key, an attacker virtually owns all of the currency in the compromised wallet. Managing cryptocurrency wallets offline, in isolated (`air-gapped') computers, has been suggested in order to secure the private keys from theft. Such air-gapped wallets are often referred to as `cold wallets.' In this paper we show how private keys can be exfiltrated from air-gapped wallets. In the adversarial attack model, the attacker infiltrates the offline wallet, infecting it with malicious code. The malware can be preinstalled or pushed in during the initial installation of the wallet, or it can infect the system when removable media (e.g., USB flash drive) is inserted into the wallet's computer in order to sign a transaction. These attack vectors have repeatedly been proven feasible in the last decade (e.g., [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]). Having obtained a foothold in the wallet, an attacker can utilize various air-gap covert channel techniques (bridgeware [11]) to jump the airgap and exfiltrate the wallet's private keys. We evaluate various exfiltration techniques, including physical, electromagnetic, electric, magnetic, acoustic, optical, and thermal techniques. This research shows that although cold wallets provide a high degree of isolation, it's not beyond the capability of motivated attackers to compromise such wallets and steal private keys from them. We demonstrate how a 256-bit private key (e.g., Bitcoin's private keys) can be exfiltrated from an offline, air-gapped wallet of a fictional character named Satoshi within a matter of seconds.
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cs.CR
Advanced Steganography and Watermarking Techniques
Grover's algorithm confers on quantum computers a quadratic advantage over classical computers for searching in an arbitrary data set, a scenario that describes Bitcoin mining. It has previously been argued that the only side-effect of quantum mining would be an increased difficulty. In this work, we argue that a crucial argument in the analysis of Bitcoin security breaks down when quantum mining is performed. Classically, a Bitcoin fork occurs rarely, i.e., when two miners find a block almost simultaneously, due to propagation time effects. The situation differs dramatically when quantum miners use Grover's algorithm, which repeatedly applies a procedure called a Grover iteration. The chances of finding a block grow quadratically with the number of Grover iterations applied. Crucially, a miner does not have to choose how many iterations to apply in advance. Suppose Alice receives Bob's new block. To maximize her revenue, she should stop and measure her state immediately in the hopes that her block (rather than Bob's) will become part of the longest chain. The strong correlation between the miners' actions and the fact that they all measure their states at the same time may lead to more forks -- which is known to be a security risk for Bitcoin. We propose a mechanism that, we conjecture, will prevent this form of quantum mining, thereby circumventing the high rate of forks.
This paper examines the time series properties of cryptocurrency assets, such as Bitcoin, using established econometric inference techniques, namely models of the GARCH family. The contribution of this study is twofold. I explore the time series properties of cryptocurrencies, a new type of financial asset on which there appears to be little or no literature. I suggest an improved econometric specification to that which has been recently proposed in Chu et al (2017), the first econometric study to examine the price dynamics of the most popular cryptocurrencies. Questions regarding the reliability of their study stem from the authors mis-diagnosing the distribution of GARCH innovations. Checks are performed on whether innovations are Gaussian or GED by using Kolmogorov type non-parametric tests and Khmaladze's martingale transformation. Null of gaussianity is strongly rejected for all GARCH(p,q) models, with $p,q \in \{1,\ldots,5 \}$, for all cryptocurrencies in sample. For tests of normality, I make use of the Gauss-Kronrod quadrature. Parameters of GARCH models are estimated with generalized error distribution innovations using maximum likelihood. For calculating P-values, the parametric bootstrap method is used. Arguing against Chu et al (2017), I show that there is a strong empirical argument against modelling innovations under some common assumptions.
This work is organized as follows. In the first section we review the prior work and we have obtained our data. Next, we will look at address reuse in the Bitcoin network. We show that a great portion of users reuse their addresses which could enable us to cluster the addresses and attribute them to single users. Next, we will categorize the nodes based on their role in the network as a customer or seller. Finally, we do a study of nodes and network performance.
Francesco Parino, Mariano G. Beiró, Laëtitia Gauvin
As the first decentralized digital currency introduced in 2009 together with the blockchain, Bitcoin offers new opportunities both for developed and developing countries. Bitcoin peer-to-peer transactions are independent of the banking system, facilitating foreign exchanges with low transaction fees, such as remittances, and offering a high degree of anonymity. These opportunities together with other key factors led the Bitcoin to become extremely popular and caused its price to skyrocket during 2017 (Henry et al. in J Digit Bank 2(4):311–337, 2018 ). However, while the Bitcoin blockchain attracts a lot of attention, it remains difficult to investigate where this attention comes from, due to the pseudo-anonymity of the system, and consequently to appreciate its social impact. Here we make an attempt to characterize the adoption of the Bitcoin blockchain by country. In the first part of the work we show that information about the number of Bitcoin software client downloads, the IP addresses that act as relays for the transactions, and the Internet searches about Bitcoin provide together a coherent picture of the system evolution in different countries. Using these quantities as a proxy for user adoption, we identify several socio-economic indexes such as the GDP per capita, freedom of trade and the Internet penetration as key variables correlated with the degree of user adoption. In the second part of the work, we build a network of Bitcoin transactions between countries using the IP addresses of nodes relaying transactions and we develop an augmented version of the gravity model of trade in order to identify socio-economic factors linked to the flow of Bitcoin between countries. In a nutshell our study provides a new insight on Bitcoin adoption by country and on the potential socio-economic drivers of the international Bitcoin flow.
Francesco Parino, Mariano G. Beiró, Laëtitia Gauvin
As the first decentralized digital currency introduced in 2009 together with\nthe blockchain, Bitcoin offers new opportunities both for developed and\ndeveloping countries. Bitcoin peer-to-peer transactions are independent of the\nbanking system, thus facilitating foreign exchanges with low transaction fees\nsuch as remittances, with a high degree of anonymity. These opportunities\ntogether with other key factors led the Bitcoin to become extremely popular and\nmade its price skyrocket during 2017. However, while the Bitcoin blockchain\nattracts a lot of attention, it remains difficult to investigate where this\nattention comes from, due to the pseudo-anonymity of the system, and\nconsequently to appreciate its social impact. Here we make an attempt to\ncharacterize the adoption of the bitcoin blockchain by country. In the first\npart of the work we show that information about the number of Bitcoin software\nclient downloads, the IP addresses that act as relays for the transactions, and\nthe Internet searches about Bitcoin provide together a coherent picture of the\nsystem evolution in different countries. Using these quantities as a proxy for\nuser adoption, we identified several socio-economic indexes such as the GDP per\ncapita, freedom of trade and the Internet penetration as key variables\ncorrelated with the degree of user adoption. In the second part of the work, we\nbuild a network of Bitcoin transactions between countries using the IP\naddresses of nodes relaying transactions and we develop an augmented version of\nthe gravity model of trade in order to identify socio-economic factors linked\nto the flow of bitcoins between countries. In a nutshell our study provides a\nnew insight on the bitcoin adoption by country and on the potential\nsocio-economic drivers of the international bitcoin flow.\n
There are limitations in client-server model of communication. Distributed architecture provides good accessibility to all the nodes in the network. A blockchain technology is follows distributed model. In the digital era, all the transactions are available in the digital form is called a ledger. This ledger belongs to all the users in the network are shared by all the users in the network. Every transaction is monitored and verified by every user in the network. The blockchain is a chain of blocks that contains a collection of transactions. Bitcoin is a cryptocurrency, depends on blockchain technology. The Bitcoins are generated from the mining of a block for the miner. Every user knows about each and every Bitcoin transaction in the blockchain network. The block is immutable, because every block is verified by each customer in the blockchain network. This is the initiation for new trend for security to the digital transactions in the world. This paper presents the logic in the blockchain and Bitcoin generation process using blockchain technology.
Mutlu Başaran Öztürk, Halil Arslan, Temur Kayhan, Mustafa Uysal
2017 yılında Bitcoin’in piyasa değerinde önemli bir artış yaşanmış ve 200 milyar dolar seviyesi aşılarak Bitcoin kurumsal yatırımcıların gündemine gelmeye başlamıştır. CME ve CBOE gibi dünyanın en büyük vadeli işlem borsaları Bitcoin’i listelerken Microsoft, PWC ve Overstock gibi kurumlar Bitcoin’i tanımlamaya başlamışlardır. Bitcoin’in bir yatırım aracı olarak görülebilmesi için bazı şartlar gereklidir. Verimli bir piyasada işlem görmesi, fiyatlama formasyonunun belirginleşmesi ve portföyler için bir çeşitlendirme aracı olabilmesi bunlardan bazıları olarak görülebilir. Ana akım varlık grupları ile Bitcoin arasındaki uzun vadeli ilişkiyi Johansen Eşbütünleşme testi ile inceleyen çalışma sonuçlarına göre Bitcoin’in altın haricinde diğer geleneksel finansal ve emtia varlıklarından bağımsız bir hareket gösterdiği ortaya çıkmıştır. Bitcoin’in söz konusu bağımsız hareketi Bitconomi olarak tanımlanırken bu durum mikro seviyede riskli bir varlığın makro anlamda portföylerin riskini düşürebileceği anlamına gelmektedir. Finansal sistemde çok küçük bir alanı işgal etmesi ve Bitcoin üretimindeki zorluk derecesinin klasik ekonomi ile çelişmesi korelasyonun anlamsız olmasının nedenleri arasında gösterilebilir. Kuzey Kore ve Ukrayna gerilimlerinde Bitcoin fiyatındaki artışlar ve altın ile Bitcoin arasındaki uzun vadeli pozitif ilişki yüksek varyansı nedeniyle eleştirilen Bitcoin’in gelecekte güvenli liman olabileceği gibi ilginç bir ironiye işaret etmektedir. Literatürdeki çalışmalar her geçen yıl Bitcoin’in varyansının gerilediğini göstermektedir.
Elli Androulaki, Artem Barger, Vita Bortnikov, Christian Cachin · 21 authors
The success of public blockchains, such as Bitcoin and Ethereum, led to growing interest in Blockchain technology and its application as a distributed system in the most innovative business use cases.
We present a detailed bubble analysis of the Bitcoin to US Dollar price dynamics from January 2012 to February 2018. We introduce a robust automatic peak detection method that classifies price time series into periods of uninterrupted market growth (drawups) and regimes of uninterrupted market decrease (drawdowns). In combination with the Lagrange Regularisation Method for detecting the beginning of a new market regime, we identify 3 major peaks and 10 additional smaller peaks, that have punctuated the dynamics of Bitcoin price during the analyzed time period. We explain this classification of long and short bubbles by a number of quantitative metrics and graphs to understand the main socio-economic drivers behind the ascent of Bitcoin over this period. Then, a detailed analysis of the growing risks associated with the three long bubbles using the Log-Periodic Power Law Singularity (LPPLS) model is based on the LPPLS Confidence Indicators, defined as the fraction of qualified fits of the LPPLS model over multiple time windows. Furthermore, for various fictitious 'present' times $t_2$ before the crashes, we employ a clustering method to group the predicted critical times $t_c$ of the LPPLS fits over different time scales, where $t_c$ is the most probable time for the ending of the bubble. Each cluster is proposed as a plausible scenario for the subsequent Bitcoin price evolution. We present these predictions for the three long bubbles and the four short bubbles that our time scale of analysis was able to resolve. Overall, our predictive scheme provides useful information to warn of an imminent crash risk.
Jakob Demant, Rasmus Munksgaard, David Décary-Hêtu, Judith Aldridge
Objective: There is broad agreement in the literature on the transformative potential of drug cryptomarkets that allow sourcing on a global market and consequently the circumvention of existing supply chains between producer and end user. We examine whether the transformative potential of drug cryptomarkets has been realized in two ways: Are cryptomarket drug sellers found in production and transit countries? and Do we see the increased use of shipping across international borders over time? Method: Using data collected by the DATACRYPTO software tool between 2013 and 2016, we characterize cryptomarket buyer behavior through the product reviews (i.e., sales transactions) posted on 15 cryptomarkets. Findings: Cryptomarket drug sellers are predominantly based in countries of Europe, North America, and Oceania. For both cannabis resin and cocaine sold on cryptomarkets, we find that known production and transit countries are not the primary sources of supplied drugs but rather key countries of consumption. In the case of 3,4-methylenedioxymethamphetamine, we observe that the Netherlands, a known production country, is the largest supplier. We further observe tendencies over time toward increased localization of cryptomarkets with regard to product destinations. Discussion: Though cryptomarkets offer a potentially global platform for drug distribution, they do not tend to be used as such. We explain our results with reference to buyers’ preferences regarding safety, risk, and convenience, alongside structural limitations for cryptomarket use such as bitcoin availability.
In this paper, by using econometric techniques we provide evidence that bitcoin exhibited the formation of speculative bubble in 2017. To conceptually rationalize the results, we delve into the extant theoretical approaches developed by Kindleberger's (1978) speculative bubbles and Minsky's (1992) financial instability hypothesis. Certainly, bitcoin has spurred a revolution in payment technology that, if treated cautiously can facilitate financial intermediation and inclusion. Ultimately, whether or not bitcoin constitutes a bubble is a decision for investors as the road to hell is paved with good promises.
We present two models of the block chain of Bitcoin in the interactive theorem prover Agda. The first one is based on a simple model of bank accounts, while having transactions with multiple inputs and outputs. The second model models transactions, which refer directly to unspent transaction outputs, rather than user accounts. The resulting blockchain gives rise to a transaction tree. That model is formalised using an extended form of induction-recursion, one of the unique features of Agda. The set of transaction trees and transactions is defined inductively, while simultaneously recursively defining the list of unspent transaction outputs. Both structures model standard transactions, coinbase transactions, transaction fees, the exact message to be signed by those spending money in a transaction, block rewards, blocks, and the blockchain, and the second structure models as well maturation time for coinbase transactions and Merkle trees. Hashing and cryptographic operations and their correctness are dealt with abstractly by postulating corresponding operations. An indication is given how the correctness of this model could be specified and proven in Agda.
Stanisław Drożdż, Robert Gȩbarowski, Ludovico Minati, Paweł Oświȩcimka · 5 authors
Based on 1-minute price changes recorded since year 2012, the fluctuation properties of the rapidly-emerging Bitcoin (BTC) market are assessed over chosen sub-periods, in terms of return distributions, volatility autocorrelation, Hurst exponents and multiscaling effects. The findings are compared to the stylized facts of mature world markets. While early trading was affected by system-specific irregularities, it is found that over the months preceding Apr 2018 all these statistical indicators approach the features hallmarking maturity. This can be taken as an indication that the Bitcoin market, and possibly other cryptocurrencies, carry concrete potential of imminently becoming a regular market, alternative to the foreign exchange (Forex). Since high-frequency price data are available since the beginning of trading, the Bitcoin offers a unique window into the statistical characteristics of a market maturation trajectory.
Turkish Abstract: Yayginlasan internet kullanimi geleneksel ticaret kavraminda degisikliklere neden olup hayatimiza yeniuygulamalar ve yeni kavramlar kazandirmistir. Bu uygulamalardan biri de e-ticarettir. E-ticaretle birlikte insanlarpara yerine alternatif odeme sekillerine yonelmislerdir. Ekonomik ve bilimsel gelisime paralel olarak para soyutlasmistir. Ozellikle son yillarda dijital ve sanal paranin kullanimini dikkat cekici bir sekilde yayginlasmistir ve Bitcoin bunun en dikkate deger orneklerinden biridir. Bitcoin; acik kaynakli bir kod olarak uretilmis kriptolu bir dijital ve bagimsiz para birimidir. Bitcoin diger para birimleri gibi, alisverislerimizde ve cevrimici ortamlarda
harcayabilecegimiz bir para birimidir. Bitcoin, merkezi bir otoriteye bagli degildir. Cunku Bitcoin merkez bankalarinin kontrolunde degil, ag uzerinde uretilmektedir. Yani yasal bir denetim soz konusu degildir. Banka araciligiyla yapilan para transferlerinde pek cok engel ortaya cikabilir. Bitcoin sisteminde haftanin her gunu ve her saatinde para transferleri hizli bir sekilde gerceklestirilir. Bitcoin hesaplari, ucretsiz olup sorgusuz sualsiz acilabilme ozelligine sahiptir. Ayrica sistem kullanici bilgileri hakkinda bilgi vermez. Bu calismada paranin tanimi, ozellikleri ve fonksiyonlari yeniden ele alinarak dijital paranin tarihsel gelisimi, sanal para konsepti ve
kripto para kavramlari degerlendirilmistir. Calismada her gecen gun daha populer hale gelen Bitcoin’in tarihsel arka plani, olumlu ve olumsuz yonleri ve piyasasi ele alinmistir.
English Abstract: The increasing use of the internet has caused changes in the concept of traditional trade and introduced new applications and new concepts to our life. One of these applications is e-commerce. With e-commerce, people have bent to alternative forms of payment instead of money. Parallel to economic and scientific development, money has been abstracted. Especially in recent years, the use of digital and virtual money has become remarkably widespread and Bitcoin is one of the most well-marked example of this. Bitcoin; is a cryptographic digital and independent currency produced as an open source code. Like other currencies, Bitcoin is a currency that we can spend in our shopping and online environments. Bitcoin is not connected to a central authority. Because Bitcoin is not under the control of the central banks, it is produced on the network. And so there is no legal control. Many obstacles may occur in the transfer of funds through the bank. On the other hand in the Bitcoin system, money transfers are carried out quickly every day and every hour of the week. Bitcoin accounts are free and opened unquestioned. In addition, the system does not provide information about user. In this study, the definition, characteristics and functions of money are reviewed and the historical development of digital money, virtual money concepts and crypto money concepts are evaluated. The historical background, positive and negative aspects and market of Bitcoin, which became more popular every day has been discussed in the study.
Masarah Paquet-Clouston, Bernhard Haslhofer, Benoît Dupont
Ransomware can prevent a user from accessing a device and its files until a ransom is paid to the attacker, most frequently in Bitcoin. With over 500 known ransomware families, it has become one of the dominant cybercrime threats for law enforcement, security professionals and the public. However, a more comprehensive, evidence-based picture on the global direct financial impact of ransomware attacks is still missing. In this paper, we present a data-driven method for identifying and gathering information on Bitcoin transactions related to illicit activity based on footprints left on the public Bitcoin blockchain. We implement this method on-top-of the GraphSense open-source platform and apply it to empirically analyze transactions related to 35 ransomware families. We estimate the lower bound direct financial impact of each ransomware family and find that, from 2013 to mid-2017, the market for ransomware payments has a minimum worth of USD 12,768,536 (22,967.54 BTC). We also find that the market is highly skewed with only a few number of players responsible for the majority of the payments. Based on these research findings, policy-makers and law enforcement agencies can use the statistics provided to understand the size of the illicit market and make informed decisions on how best to address the threat.