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1. The rise and fall of cryptocurrencies

   Feder, Amir ; Gandal, Neil ; Hamrick, JT ; Moore, Tyler ; Vasek, Marie ( June 2018 , Workshop on the Economics of Information Security)

   Since Bitcoin’s introduction in 2009, interest in cryptocurrencies has soared. One manifestation of this interest has been the explosion of newly created coins. This paper examines the dynamics of coin creation, competition and destruction in the cryptocurrency industry. In order to conduct the analysis, we develop a methodology to identify peaks in prices and trade volume, as well as when coins are abandoned and subsequently “resurrected”. We study trading activity associated with 1 082 coins over a nearly five-year period. We present evidence that the more frequently traded coins experience the biggest price rises. They are also much less likely to be abandoned, that is, to experience a drop in average trading volume to below 1% of a prior peak value. Overall, we find that 44% of publicly-traded coins are abandoned, at least temporarily. 71% of abandoned coins are later resurrected, leaving 18% of coins to fail permanently. We then examine the association between entry and exit and other key variables such as price, volume, and market capitalization in order to analyze and provide intuition underpinning the fundamentals in this market. We conclude by examining the bursting of the Bitcoin bubble in December 2017. Unlike the end of the 2013 bubble, some alternative cryptocurrencies continue to flourish after the fall of Bitcoin. 

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2. On the role of local blockchain network features in cryptocurrency price formation

   https://doi.org/10.1002/cjs.11547  

   Dey, Asim K. ; Akcora, Cuneyt G. ; Gel, Yulia R. ; Kantarcioglu, Murat ( March 2020 , Canadian Journal of Statistics)

   Cryptocurrencies and the underpinning blockchain technology have gained unprecedented public attention recently. In contrast to fiat currencies, transactions of cryptocurrencies, such as Bitcoin and Litecoin, are permanently recorded on distributed ledgers to be seen by the public. As a result, public availability of all cryptocurrency transactions allows us to create a complex network of financial interactions that can be used to study not only the blockchain graph, but also the relationship between various blockchain network features and cryptocurrency risk investment. We introduce a novel concept of chainlets, or blockchain motifs, to utilize this information. Chainlets allow us to evaluate the role of local topological structure of the blockchain on the joint Bitcoin and Litecoin price formation and dynamics. We investigate the predictive Granger causality of chainlets and identify certain types of chainlets that exhibit the highest predictive influence on cryptocurrency price and investment risk. More generally, while statistical aspects of blockchain data analytics remain virtually unexplored, the paper aims to highlight various emerging theoretical, methodological and applied research challenges of blockchain data analysis that will be of interest to the broad statistical community.The Canadian Journal of Statistics48: 561–581; 2020 © 2020 Statistical Society of Canada

    

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3. MineSweeper: An In-depth Look into Drive-by Cryptocurrency Mining and Its Defense

   https://doi.org/10.1145/3243734.3243858  

   Konoth, Radhesh Krishnan ; Vineti, Emanuele ; Moonsamy, Veelasha ; Lindorfer, Martina ; Kruegel, Christopher ; Bos, Herbert ; Vigna, Giovanni ( October 2018 , 2018 ACM SIGSAC Conference on Computer and Communications Security)

   A wave of alternative coins that can be effectively mined without specialized hardware, and a surge in cryptocurrencies' market value has led to the development of cryptocurrency mining ( cryptomining ) services, such as Coinhive, which can be easily integrated into websites to monetize the computational power of their visitors. While legitimate website operators are exploring these services as an alternative to advertisements, they have also drawn the attention of cybercriminals: drive-by mining (also known as cryptojacking ) is a new web-based attack, in which an infected website secretly executes JavaScript code and/or a WebAssembly module in the user's browser to mine cryptocurrencies without her consent. In this paper, we perform a comprehensive analysis on Alexa's Top 1 Million websites to shed light on the prevalence and profitability of this attack. We study the websites affected by drive-by mining to understand the techniques being used to evade detection, and the latest web technologies being exploited to efficiently mine cryptocurrency. As a result of our study, which covers 28 Coinhive-like services that are widely being used by drive-by mining websites, we identified 20 active cryptomining campaigns. Motivated by our findings, we investigate possible countermeasures against this type of attack. We discuss how current blacklisting approaches and heuristics based on CPU usage are insufficient, and present MineSweeper, a novel detection technique that is based on the intrinsic characteristics of cryptomining code, and, thus, is resilient to obfuscation. Our approach could be integrated into browsers to warn users about silent cryptomining when visiting websites that do not ask for their consent. 

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4. Cryptocurrency Competition and Market Concentration in the Presence of Network Effects

   https://doi.org/https://doi.org/10.5195/ledger.2021.226  

   stylianou, kostantinos ; spiegelberg, leonhard ; herlihy, maurice ; carter, nic ( October 2021 , Ledger)

   null (Ed.)

   When network products and services become more valuable as their userbase grows (network effects), this tendency can become a major determinant of how they compete with each other in the market and how the market is structured. Network effects are traditionally linked to high market concentration, early-mover advantages, and entry barriers, and in the market they have also been used as a valuation tool. The recent resurgence of Bitcoin has been partly attributed to network effects, too. We study the existence of network effects in six cryptocurrencies from their inception to obtain a high-level overview of the application of network effects in the cryptocurrency market. We show that, contrary to the usual implications of network effects, they do not serve to concentrate the cryptocurrency market, nor do they accord any one cryptocurrency a definitive competitive advantage, nor are they consistent enough to be reliable valuation tools. Therefore, while network effects do occur in cryptocurrency networks, they are not (yet) a defining feature of the cryptocurrency market as a whole. 

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5. Minimizing Trust in Hardware Wallets with Two Factor Signatures

   Marcedone, Antonio ; Pass, Rafael ; shelat, abhi ( January 2019 , Financial Crypto)

   We introduce the notion of two-factor signatures (2FS), a generalization of a two-out-of-two threshold signature scheme in which one of the parties is a hardware token which can store a high-entropy secret, and the other party is a human who knows a low-entropy password. The security (unforgeability) property of 2FS requires that an external adversary corrupting either party (the token or the computer the human is using) cannot forge a signature. This primitive is useful in contexts like hardware cryptocurrency wallets in which a signature conveys the authorization of a transaction. By the above security property, a hardware wallet implementing a two-factor signature scheme is secure against attacks mounted by a malicious hardware vendor; in contrast, all currently used wallet systems break under such an attack (and as such are not secure under our definition). We construct efficient provably-secure 2FS schemes which produce either Schnorr signature (assuming the DLOG assumption), or EC-DSA signatures (assuming security of EC-DSA and the CDH assumption) in the Random Oracle Model, and evaluate the performance of implementations of them. Our EC-DSA based 2FS scheme can directly replace currently used hardware wallets for Bitcoin and other major cryptocurrencies to enable security against malicious hardware vendors. 

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