Ripple Protocol Vs Xrp
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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. -
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. -
Read the Report Brief
A REVOLUTION IN TRUST Distributed Ledger Technology in Relief & Development MAY 2017 “The principal challenge associated with [DLT] is a lack of awareness of the technology, especially in sectors other than banking, and a lack of widespread understanding of how it works.” - Deloitte Executive Summary1 The Upside In 2016, the blockchain was recognized as one of the top 10 In a recent report, Accenture surveyed emerging technologies by the World Economic Forum.2 The cost data from eight of the world’s ten potential of the blockchain and distributed ledger technology largest investment banks, with the goal of putting a dollar figure against potential (hereinafter “DLT”) to deliver benefits is significant. Gartner cost savings that might be achieved with estimates that DLT will result in $176 billion in added business DLT. The report concluded that the value by 2025; that total reaches $3.1 trillion by 2030.3 banks analyzed could reduce infrastructure costs by an average $8 to Investment in the field reflects the widespread belief that the $12 billion a year. The survey mapped technology can deliver value. Numerous trials, and some more than 50 operational cost metrics deployments, can be found across multiple sectors. and found the savings would break down as follows: Over two dozen countries are investing in DLT 70% savings on central financial More than 2,500 patents have been filed in the last 3 reporting 4 30-50% savings on compliance years 50% savings on centralized operations As of Q4, 2016, 28 of the top 30 banks were engaged in 50% savings on business blockchain proofs-of-concept operations. -
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. -
Mckinsey on Payments
Volume 8, Number 21 May 2015 McKinsey on Payments Foreword 1 Gauging the disruptive potential of digital wallets 3 While they have established a solid foundation for growth, digital wallets are by no means a guaranteed success. They must continue to evolve if they are to have a truly disruptive impact on the payments landscape. Providers can improve their chances by focusing on six “markers” for success in payments innovation. New partnership models in transaction banking 11 A number of trends are leading to a fundamental rethinking of the traditional model by which banks offer transaction banking services to clients outside their established markets. Four distinct partnership models offer the best opportunities for banks seeking to succeed in an evolving landscape. Toward an Internet of Value: An interview with Chris Larsen, 19 CEO of Ripple Labs McKinsey on Payments sits down with the co-founder of Ripple Labs to discuss the nuts and bolts of the Ripple protocol, the implications for the correspondent banking model, and the emergence of an “Internet of Value.” Faster payments: Building a business, not just an infrastructure 23 A faster payments infrastructure is not an end in itself, it is an opportunity for banks to deliver innovative products and services in both consumer and corporate payments. To monetize this opportunity, financial institutions should focus relentlessly on design, customer experience, accessibility and convenience. Toward an Internet of Value: An interview with Chris Larsen , CEO of Ripple Labs Chris Larsen is co-founder and chief executive officer of Ripple Labs, a soft - ware firm that developed and continues to support the open-source Ripple protocol. -
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. -
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 -
Thai Perception on Litecoin Value Toby Gibbs, Suwaree Yordchim
World Academy of Science, Engineering and Technology International Journal of Economics and Management Engineering Vol:8, No:8, 2014 Thai Perception on Litecoin Value Toby Gibbs, Suwaree Yordchim Abstract—This research analyzes factors affecting the success of include greater resistance to a double spending attack over the Litecoin Value within Thailand and develops a guideline for self- same period as Bitcoin, if both networks had the same reliance for effective business implementation. Samples in this study computing power. included 119 people through surveys. The results revealed four main Litecoin uses scrypt in its proof-of-work algorithm: A factors affecting the success as follows: 1) Future Career training should be pursued in applied Litecoin development. 2) Didn't grasp sequential memory-hard function requiring asymptotically the concept of a digital currency or see the benefit of a digital more memory than an algorithm which is not memory-hard. currency. 3) There is a great need to educate the next generation of The Litecoin network will produce 84 million Litecoins, or learners on the benefits of Litecoin within the community. 4) A great four times as many currency units as will be issued by the majority didn't know what Litecoin was. Bitcoin network. The guideline for self-reliance planning consisted of 4 aspects: 1) The original intended purpose of using scrypt was to allow Development planning: by arranging meet up groups to conduct further education on Litecoin and share solutions on adoption into miners to mine both Bitcoin and Litecoin at the same time. every day usage. Local communities need to develop awareness of The choice to use scrypt was also partially to avoid giving the usefulness of Litecoin and share the value of Litecoin among advantage to video card, FPGA and ASIC miners over CPU friends and family. -
Evolution Or Revolution? Distributed Ledger Technologies in Financial Services
Evolution or revolution? Distributed ledger technologies in financial services Anil Savio Kavuri1 and Alistair Milne2 (There are two versions of this paper: a short summary report of 16 pages plus references; the full research report of 121 pages plus references.) 1 Loughborough University and Australian National University. [email protected] 2 Loughborough University. [email protected] Evolution or revolution? Distributed ledger technologies in financial services Contents of full report 1 Introduction to the full report ............................................................................................... 2 2 Distributed ledgers: basic concepts and supporting technologies. ...................................... 5 2.1 Definitions ....................................................................................................................... 5 2.2 The component technologies used in distributed ledgers ............................................. 7 2.3 How the technologies are combined: the database ‘stack’ ........................................... 8 3 Applications of distributed ledgers in financial services ..................................................... 11 3.1 Fourteen areas of application....................................................................................... 11 3.2 Seven case studies ........................................................................................................ 38 4 Distributed ledgers: the adoption decision ........................................................................