Ripple: Overview and Outlook
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Linking Wallets and Deanonymizing Transactions in the Ripple Network
Proceedings on Privacy Enhancing Technologies ; 2016 (4):436–453 Pedro Moreno-Sanchez*, Muhammad Bilal Zafar, and Aniket Kate* Listening to Whispers of Ripple: Linking Wallets and Deanonymizing Transactions in the Ripple Network Abstract: The decentralized I owe you (IOU) transac- 1 Introduction tion network Ripple is gaining prominence as a fast, low- cost and efficient method for performing same and cross- In recent years, we have observed a rather unexpected currency payments. Ripple keeps track of IOU credit its growth of IOU transaction networks such as Ripple [36, users have granted to their business partners or friends, 40]. Its pseudonymous nature, ability to perform multi- and settles transactions between two connected Ripple currency transactions across the globe in a matter of wallets by appropriately changing credit values on the seconds, and potential to monetize everything [15] re- connecting paths. Similar to cryptocurrencies such as gardless of jurisdiction have been pivotal to their suc- Bitcoin, while the ownership of the wallets is implicitly cess so far. In a transaction network [54, 55, 59] such as pseudonymous in Ripple, IOU credit links and transac- Ripple [10], users express trust in each other in terms tion flows between wallets are publicly available in an on- of I Owe You (IOU) credit they are willing to extend line ledger. In this paper, we present the first thorough each other. This online approach allows transactions in study that analyzes this globally visible log and charac- fiat money, cryptocurrencies (e.g., bitcoin1) and user- terizes the privacy issues with the current Ripple net- defined currencies, and improves on some of the cur- work. -
On the Relationship of Cryptocurrency Price with US Stock and Gold Price Using Copula Models
mathematics Article On the Relationship of Cryptocurrency Price with US Stock and Gold Price Using Copula Models Jong-Min Kim 1 , Seong-Tae Kim 2 and Sangjin Kim 3,* 1 Statistics Discipline, University of Minnesota at Morris, Morris, MN 56267, USA; [email protected] 2 Department of Mathematics, North Carolina A&T State University, Greensboro, NC 27411, USA; [email protected] 3 Department of Management and Information Systems, Dong-A University, Busan 49236, Korea * Correspondence: [email protected] Received: 15 September 2020; Accepted: 20 October 2020; Published: 23 October 2020 Abstract: This paper examines the relationship of the leading financial assets, Bitcoin, Gold, and S&P 500 with GARCH-Dynamic Conditional Correlation (DCC), Nonlinear Asymmetric GARCH DCC (NA-DCC), Gaussian copula-based GARCH-DCC (GC-DCC), and Gaussian copula-based Nonlinear Asymmetric-DCC (GCNA-DCC). Under the high volatility financial situation such as the COVID-19 pandemic occurrence, there exist a computation difficulty to use the traditional DCC method to the selected cryptocurrencies. To solve this limitation, GC-DCC and GCNA-DCC are applied to investigate the time-varying relationship among Bitcoin, Gold, and S&P 500. In terms of log-likelihood, we show that GC-DCC and GCNA-DCC are better models than DCC and NA-DCC to show relationship of Bitcoin with Gold and S&P 500. We also consider the relationships among time-varying conditional correlation with Bitcoin volatility, and S&P 500 volatility by a Gaussian Copula Marginal Regression (GCMR) model. The empirical findings show that S&P 500 and Gold price are statistically significant to Bitcoin in terms of log-return and volatility. -
Vulnerability of Blockchain Technologies to Quantum Attacks
Vulnerability of Blockchain Technologies to Quantum Attacks Joseph J. Kearneya, Carlos A. Perez-Delgado a,∗ aSchool of Computing, University of Kent, Canterbury, Kent CT2 7NF United Kingdom Abstract Quantum computation represents a threat to many cryptographic protocols in operation today. It has been estimated that by 2035, there will exist a quantum computer capable of breaking the vital cryptographic scheme RSA2048. Blockchain technologies rely on cryptographic protocols for many of their essential sub- routines. Some of these protocols, but not all, are open to quantum attacks. Here we analyze the major blockchain-based cryptocurrencies deployed today—including Bitcoin, Ethereum, Litecoin and ZCash, and determine their risk exposure to quantum attacks. We finish with a comparative analysis of the studied cryptocurrencies and their underlying blockchain technologies and their relative levels of vulnerability to quantum attacks. Introduction exist to allow the legitimate owner to recover this account. Blockchain systems are unlike other cryptosys- tems in that they are not just meant to protect an By contrast, in a blockchain system, there is no information asset. A blockchain is a ledger, and as central authority to manage users’ access keys. The such it is the asset. owner of a resource is by definition the one hold- A blockchain is secured through the use of cryp- ing the private encryption keys. There are no of- tographic techniques. Notably, asymmetric encryp- fline backups. The blockchain, an always online tion schemes such as RSA or Elliptic Curve (EC) cryptographic system, is considered the resource— cryptography are used to generate private/public or at least the authoritative description of it. -
Blocksci: Design and Applications of a Blockchain Analysis Platform
BlockSci: Design and applications of a blockchain analysis platform Harry Kalodner Steven Goldfeder Alishah Chator [email protected] [email protected] [email protected] Princeton University Princeton University Johns Hopkins University Malte Möser Arvind Narayanan [email protected] [email protected] Princeton University Princeton University ABSTRACT to partition eectively. In fact, we conjecture that the use of a tra- Analysis of blockchain data is useful for both scientic research ditional, distributed transactional database for blockchain analysis and commercial applications. We present BlockSci, an open-source has innite COST [5], in the sense that no level of parallelism can software platform for blockchain analysis. BlockSci is versatile in outperform an optimized single-threaded implementation. its support for dierent blockchains and analysis tasks. It incorpo- BlockSci comes with batteries included. First, it is not limited rates an in-memory, analytical (rather than transactional) database, to Bitcoin: a parsing step converts a variety of blockchains into making it several hundred times faster than existing tools. We a common, compact format. Currently supported blockchains in- describe BlockSci’s design and present four analyses that illustrate clude Bitcoin, Litecoin, Namecoin, and Zcash (Section 2.1). Smart its capabilities. contract platforms such as Ethereum are outside our scope. Second, This is a working paper that accompanies the rst public release BlockSci includes a library of useful analytic and visualization tools, of BlockSci, available at github.com/citp/BlockSci. We seek input such as identifying special transactions (e.g., CoinJoin) and linking from the community to further develop the software and explore addresses to each other based on well-known heuristics (Section other potential applications. -
Using Blockchain Technology to Secure the Internet of Things
Using Blockchain Technology to Secure the Internet of Things Presented by the Blockchain/ Distributed Ledger Working Group © 2018 Cloud Security Alliance – All Rights Reserved. You may download, store, display on your computer, view, print, and link to Using Blockchain Technology to Secure the Internet of Things subject to the following: (a) the Document may be used solely for your personal, informational, non- commercial use; (b) the Report may not be modified or altered in any way; (c) the Document may not be redistributed; and (d) the trademark, copyright or other notices may not be removed. You may quote portions of the Document as permitted by the Fair Use provisions of the United States Copyright Act, provided that you attribute the portions to the Using Blockchain Technology to Secure the Internet of Things paper. Blockchain/Distributed Ledger Technology Working Group | Using Blockchain Technology to Secure the Internet of Things 2 © Copyright 2018, Cloud Security Alliance. All rights reserved. ABOUT CSA The Cloud Security Alliance is a not-for-profit organization with a mission to promote the use of best practices for providing security assurance within Cloud Computing, and to provide education on the uses of Cloud Computing to help secure all other forms of computing. The Cloud Security Alliance is led by a broad coalition of industry practitioners, corporations, associations and other key stakeholders. For further information, visit us at www.cloudsecurityalliance.org and follow us on Twitter @cloudsa. Blockchain/Distributed Ledger Technology Working Group | Using Blockchain Technology to Secure the Internet of Things 3 © Copyright 2018, Cloud Security Alliance. All rights reserved. -
Merged Mining: Curse Or Cure?
Merged Mining: Curse or Cure? Aljosha Judmayer, Alexei Zamyatin, Nicholas Stifter, Artemios Voyiatzis, Edgar Weippl SBA Research, Vienna, Austria (firstletterfirstname)(lastname)@sba-research.org Abstract: Merged mining refers to the concept of mining more than one cryp- tocurrency without necessitating additional proof-of-work effort. Although merged mining has been adopted by a number of cryptocurrencies already, to this date lit- tle is known about the effects and implications. We shed light on this topic area by performing a comprehensive analysis of merged mining in practice. As part of this analysis, we present a block attribution scheme for mining pools to assist in the evaluation of mining centralization. Our findings disclose that mining pools in merge-mined cryptocurrencies have operated at the edge of, and even beyond, the security guarantees offered by the underlying Nakamoto consensus for ex- tended periods. We discuss the implications and security considerations for these cryptocurrencies and the mining ecosystem as a whole, and link our findings to the intended effects of merged mining. 1 Introduction The topic of merged mining has received little attention from the scientific community, despite having been actively employed by a number of cryptocurrencies for several years. New and emerging cryptocurrencies such as Rootstock continue to consider and expand on the concept of merged mining in their designs to this day [19]. Merged min- ing refers to the process of searching for proof-of-work (PoW) solutions for multiple cryptocurrencies concurrently without requiring additional computational resources. The rationale behind merged mining lies in leveraging on the computational power of different cryptocurrencies by bundling their resources instead of having them stand in direct competition, and also to serve as a bootstrapping mechanism for small and fledgling networks [27, 33]. -
Decentralized Reputation Model and Trust Framework Blockchain and Smart Contracts
IT 18 062 Examensarbete 30 hp December 2018 Decentralized Reputation Model and Trust Framework Blockchain and Smart contracts Sujata Tamang Institutionen för informationsteknologi Department of Information Technology Abstract Decentralized Reputation Model and Trust Framework: Blockchain and Smart contracts Sujata Tamang Teknisk- naturvetenskaplig fakultet UTH-enheten Blockchain technology is being researched in diverse domains for its ability to provide distributed, decentralized and time-stamped Besöksadress: transactions. It is attributed to by its fault-tolerant and zero- Ångströmlaboratoriet Lägerhyddsvägen 1 downtime characteristics with methods to ensure records of immutable Hus 4, Plan 0 data such that its modification is computationally infeasible. Trust frameworks and reputation models of an online interaction system are Postadress: responsible for providing enough information (e.g., in the form of Box 536 751 21 Uppsala trust score) to infer the trustworthiness of interacting entities. The risk of failure or probability of success when interacting with an Telefon: entity relies on the information provided by the reputation system. 018 – 471 30 03 Thus, it is crucial to have an accurate, reliable and immutable trust Telefax: score assigned by the reputation system. The centralized nature of 018 – 471 30 00 current trust systems, however, leaves the valuable information as such prone to both external and internal attacks. This master's thesis Hemsida: project, therefore, studies the use of blockchain technology as an http://www.teknat.uu.se/student infrastructure for an online interaction system that can guarantee a reliable and immutable trust score. It proposes a system of smart contracts that specify the logic for interactions and models trust among pseudonymous identities of the system. -
A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets
Journal of Risk and Financial Management Review A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets Nikolaos A. Kyriazis Department of Economics, University of Thessaly, 38333 Volos, Greece; [email protected] Abstract: This study is an integrated survey of GARCH methodologies applications on 67 empirical papers that focus on cryptocurrencies. More sophisticated GARCH models are found to better explain the fluctuations in the volatility of cryptocurrencies. The main characteristics and the optimal approaches for modeling returns and volatility of cryptocurrencies are under scrutiny. Moreover, emphasis is placed on interconnectedness and hedging and/or diversifying abilities, measurement of profit-making and risk, efficiency and herding behavior. This leads to fruitful results and sheds light on a broad spectrum of aspects. In-depth analysis is provided of the speculative character of digital currencies and the possibility of improvement of the risk–return trade-off in investors’ portfolios. Overall, it is found that the inclusion of Bitcoin in portfolios with conventional assets could significantly improve the risk–return trade-off of investors’ decisions. Results on whether Bitcoin resembles gold are split. The same is true about whether Bitcoins volatility presents larger reactions to positive or negative shocks. Cryptocurrency markets are found not to be efficient. This study provides a roadmap for researchers and investors as well as authorities. Keywords: decentralized cryptocurrency; Bitcoin; survey; volatility modelling Citation: Kyriazis, Nikolaos A. 2021. A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets. Journal of Risk and 1. Introduction Financial Management 14: 293. The continuing evolution of cryptocurrency markets and exchanges during the last few https://doi.org/10.3390/jrfm years has aroused sparkling interest amid academic researchers, monetary policymakers, 14070293 regulators, investors and the financial press. -
Ethereum Classic Price Prediction 2030
1 Ethereum Classic Price Prediction 2030 Update [06-08-2021] There are various cryptocurrencies out now in the bitcoin market, and people worldwide and mostly in the countries like United States , are investing in these digital currencies. 00000001 Ethereum max 7d low Emax 7d high- 0. And this particular blockchain allows to grants investors security and also control for all of their digital assets. Firstly, we have to be sure about the amount of ETH in our wallet to cover our transaction fees. Once OKExChain supports EVM, developers can use the development tools and languages of Ethereum to develop smart contracts on OKExChain. The contract launched the Beacon Chain, the first stage in the ETH 2. Most are confident that Ethereum 2. Ethereum s Growing Transaction Fees Shouldn t Stop Users. Is Cardano or Ethereum a Better Investment. It was developed in 2017 by Charles Hoskinson, who was previously involved in creating Ethereum itself. In other words, we have defined proof, in the per-coin values of both Bitcoin and Ethereum, that increases of 500 , 1,000 and more are not unprecedented or wildly unreasonable in this market , especially for coins that started out at a few cents. And this has given the latter a significant advantage over the former. At the same time, it is also going to take many other alts with it to new highs. A 10k price is definitely on the cards with so many Decentralized finance apps shifting to their protocols. If Ethereum could hit 10k by the end of 2021 then it would cross the 1 trillion market cap and might become the 2nd cryptocurrency to do so. -
Impossibility of Full Decentralization in Permissionless Blockchains
Impossibility of Full Decentralization in Permissionless Blockchains Yujin Kwon*, Jian Liuy, Minjeong Kim*, Dawn Songy, Yongdae Kim* *KAIST {dbwls8724,mjkim9394,yongdaek}@kaist.ac.kr yUC Berkeley [email protected],[email protected] ABSTRACT between achieving good decentralization in the consensus protocol Bitcoin uses the proof-of-work (PoW) mechanism where nodes earn and not relying on a TTP exists. rewards in return for the use of their computing resources. Although this incentive system has attracted many participants, power has, CCS CONCEPTS at the same time, been significantly biased towards a few nodes, • Security and privacy → Economics of security and privacy; called mining pools. In addition, poor decentralization appears not Distributed systems security; only in PoW-based coins but also in coins that adopt proof-of-stake (PoS) and delegated proof-of-stake (DPoS) mechanisms. KEYWORDS In this paper, we address the issue of centralization in the consen- Blockchain; Consensus Protocol; Decentralization sus protocol. To this end, we first define ¹m; ε; δº-decentralization as a state satisfying that 1) there are at least m participants running 1 INTRODUCTION a node, and 2) the ratio between the total resource power of nodes Traditional currencies have a centralized structure, and thus there run by the richest and the δ-th percentile participants is less than exist several problems such as a single point of failure and corrup- or equal to 1 + ε. Therefore, when m is sufficiently large, and ε and tion. For example, the global financial crisis in 2008 was aggravated δ are 0, ¹m; ε; δº-decentralization represents full decentralization, by the flawed policies of banks that eventually led to many bank which is an ideal state. -
Exploring the Interconnectedness of Cryptocurrencies Using Correlation Networks
Exploring the Interconnectedness of Cryptocurrencies using Correlation Networks Andrew Burnie UCL Computer Science Doctoral Student at The Alan Turing Institute [email protected] Conference Paper presented at The Cryptocurrency Research Conference 2018, 24 May 2018, Anglia Ruskin University Lord Ashcroft International Business School Centre for Financial Research, Cambridge, UK. Abstract Correlation networks were used to detect characteristics which, although fixed over time, have an important influence on the evolution of prices over time. Potentially important features were identified using the websites and whitepapers of cryptocurrencies with the largest userbases. These were assessed using two datasets to enhance robustness: one with fourteen cryptocurrencies beginning from 9 November 2017, and a subset with nine cryptocurrencies starting 9 September 2016, both ending 6 March 2018. Separately analysing the subset of cryptocurrencies raised the number of data points from 115 to 537, and improved robustness to changes in relationships over time. Excluding USD Tether, the results showed a positive association between different cryptocurrencies that was statistically significant. Robust, strong positive associations were observed for six cryptocurrencies where one was a fork of the other; Bitcoin / Bitcoin Cash was an exception. There was evidence for the existence of a group of cryptocurrencies particularly associated with Cardano, and a separate group correlated with Ethereum. The data was not consistent with a token’s functionality or creation mechanism being the dominant determinants of the evolution of prices over time but did suggest that factors other than speculation contributed to the price. Keywords: Correlation Networks; Interconnectedness; Contagion; Speculation 1 1. Introduction The year 2017 saw the start of a rapid diversification in cryptocurrencies. -
The Relationship Between the Popularity of Cryptocurrencies and Their Prices, Returns and Trading Volumes: a Structural Break An
İstanbul İktisat Dergisi - Istanbul Journal of Economics 69, 2019/2, s. 133-157 ISSN: 2602-4152 E-ISSN: 2602-3954 RESEARCH ARTICLE / ARAŞTIRMA MAKALESİ The Relationship Between the Popularity of Cryptocurrencies and their Prices, Returns and Trading Volumes: A Structural Break and Comparative Analysis Kripto Paraların Bilinirliği ile Fiyat, Getiri ve İşlem Hacimleri Arasındaki İlişki: Yapısal Kırılmalı ve Karşılaştırmalı Bir Analiz Mustafa ÖZYEŞİL1 ABSTRACT In this study, the relationship between the popularity of cryptocurrencies and their price, return and trading volumes are examined through time series analysis. The popularity variable is determined according the frequency of cryptocurrencies being DOI: 10.26650/ISTJECON2019-0017 searched on the internet. Stationarity of series is examined by Vogelsang and Perron (1998) structural breaks ADF unit root test. According to the test results, all series are found to be stationary at level values. VAR analyses and impulse-response functions are performed to reveal dynamic interaction between the series. 1Assist. Prof. Dr., Istanbul Aydın University, According to impulse - response test results, returns of BITCOIN Anadolu BIL Vocational School, Department of Business Administration, Istanbul, Turkey decreased against a decreasing shock in the number searches on the internet and its price and trading volume followed a ORCID: M.Ö. 0000-0002-4442-7087 fluctuating course. In order to see the causality relationship Corresponding author/Sorumlu yazar: between variables the Granger causality test