Beyond Bitcoin: a Critical Look at Blockchain-Based Systems
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Useful Computation on the Block Chain The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Yeung, Fuk. 2019. Useful Computation on the Block Chain. Master's thesis, Harvard Extension School. Citable link https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37364565 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA 111 Useful Computation on the Block Chain Fuk Yeung A Thesis in the Field of Information Technology for the Degree of Master of Liberal Arts in Extension Studies Harvard University November 2019 Copyright 2019 [Fuk Yeung] Abstract The recent growth of blockchain technology and its usage has increased the size of cryptocurrency networks. However, this increase has come at the cost of high energy consumption due to the processing power needed to maintain large cryptocurrency networks. In the largest networks, this processing power is attributed to wasted computations centered around solving a Proof of Work algorithm. There have been several attempts to address this problem and it is an area of continuing improvement. We will present a summary of proposed solutions as well as an in-depth look at a promising alternative algorithm known as Proof of Useful Work. This solution will redirect wasted computation towards useful work. We will show that this is a viable alternative to Proof of Work. Dedication Thank you to everyone who has supported me throughout the process of writing this piece. -
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. -
Beauty Is Not in the Eye of the Beholder
Insight Consumer and Wealth Management Digital Assets: Beauty Is Not in the Eye of the Beholder Parsing the Beauty from the Beast. Investment Strategy Group | June 2021 Sharmin Mossavar-Rahmani Chief Investment Officer Investment Strategy Group Goldman Sachs The co-authors give special thanks to: Farshid Asl Managing Director Matheus Dibo Shahz Khatri Vice President Vice President Brett Nelson Managing Director Michael Murdoch Vice President Jakub Duda Shep Moore-Berg Harm Zebregs Vice President Vice President Vice President Shivani Gupta Analyst Oussama Fatri Yousra Zerouali Vice President Analyst ISG material represents the views of ISG in Consumer and Wealth Management (“CWM”) of GS. It is not financial research or a product of GS Global Investment Research (“GIR”) and may vary significantly from those expressed by individual portfolio management teams within CWM, or other groups at Goldman Sachs. 2021 INSIGHT Dear Clients, There has been enormous change in the world of cryptocurrencies and blockchain technology since we first wrote about it in 2017. The number of cryptocurrencies has increased from about 2,000, with a market capitalization of over $200 billion in late 2017, to over 8,000, with a market capitalization of about $1.6 trillion. For context, the market capitalization of global equities is about $110 trillion, that of the S&P 500 stocks is $35 trillion and that of US Treasuries is $22 trillion. Reported trading volume in cryptocurrencies, as represented by the two largest cryptocurrencies by market capitalization, has increased sixfold, from an estimated $6.8 billion per day in late 2017 to $48.6 billion per day in May 2021.1 This data is based on what is called “clean data” from Coin Metrics; the total reported trading volume is significantly higher, but much of it is artificially inflated.2,3 For context, trading volume on US equity exchanges doubled over the same period. -
Piecework: Generalized Outsourcing Control for Proofs of Work
(Short Paper): PieceWork: Generalized Outsourcing Control for Proofs of Work Philip Daian1, Ittay Eyal1, Ari Juels2, and Emin G¨unSirer1 1 Department of Computer Science, Cornell University, [email protected],[email protected],[email protected] 2 Jacobs Technion-Cornell Institute, Cornell Tech [email protected] Abstract. Most prominent cryptocurrencies utilize proof of work (PoW) to secure their operation, yet PoW suffers from two key undesirable prop- erties. First, the work done is generally wasted, not useful for anything but the gleaned security of the cryptocurrency. Second, PoW is natu- rally outsourceable, leading to inegalitarian concentration of power in the hands of few so-called pools that command large portions of the system's computation power. We introduce a general approach to constructing PoW called PieceWork that tackles both issues. In essence, PieceWork allows for a configurable fraction of PoW computation to be outsourced to workers. Its controlled outsourcing allows for reusing the work towards additional goals such as spam prevention and DoS mitigation, thereby reducing PoW waste. Meanwhile, PieceWork can be tuned to prevent excessive outsourcing. Doing so causes pool operation to be significantly more costly than today. This disincentivizes aggregation of work in mining pools. 1 Introduction Distributed cryptocurrencies such as Bitcoin [18] rely on the equivalence \com- putation = money." To generate a batch of coins, clients in a distributed cryp- tocurrency system perform an operation called mining. Mining requires solving a computationally intensive problem involving repeated cryptographic hashing. Such problem and its solution is called a Proof of Work (PoW) [11]. As currently designed, nearly all PoWs suffer from one of two drawbacks (or both, as in Bitcoin). -
State of the Art: the Monero Cryptocurrency Mining Malware Detection Using Supervised Machine Learning Algorithms
International Journal of Applied Science and Engineering State of the art: The monero cryptocurrency mining malware detection using supervised machine learning algorithms Wilfridus Bambang Triadi Handaya1*, Mohd Najwadi Yusoff 2, Aman Jantan2 1 Department of Informatics, Universitas Atma Jaya Yogyakarta, Daerah Istimewa Yogyakarta, Indonesia 2 School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia ABSTRACT Today’s evolving information technology trend is fuelling increasingly various cybercrime. Various cybercrime types, such as malware attacks and data breach activities, organizations, and countries, occur every day. Malware is one of the biggest cyber threats on the Internet today. Every year, the number of data breaches continues to increase. Mining is a complete cryptocurrency network’s computing process to verify transaction records, called blockchains, and receive digital coins in return. This mining process requires severe hardware and significant CPU resources to create cryptocurrencies. A statistic published by Statista in mid-2020 about the most detected crypto-mining malware types influencing corporate networks global from January to June 2020, it can be seen that cryptocurrency mining activity leading to the pool of Monero amounts to 46% derived from the use of XMRig. Malware detection is like an endless war between malware authors and malware prevention vendors. This trend change also makes the procedures and forms of analysis must adapt. From previously done manually with various tools for static analysis, to be OPEN ACCESS subsequently replaced with automatic analysis through the application of machine learning algorithms. Received: October 9, 2020 Revised: December 20, 2020 Keywords: Malware detection, XMRig, Monero, Cryptocurrencies, Mining. Accepted: January 6, 2021 Corresponding Author: Wilfridus Bambang Triadi Handaya 1. -
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. -
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]. -
Alternative Mining Puzzles
Cryptocurrency Technologies Alternative Mining Puzzles Alternative Mining Puzzles • Essential Puzzle Requirements • ASIC-Resistant Puzzles • Proof-of-Useful-Work • Non-outsourceable Puzzles • Proof-of-Stake “Virtual Mining” Puzzles (recap) Incentive system steers participants Basic features of Bitcoin’s puzzle The puzzle is difficult to solve, so attacks are costly … but not too hard, so honest miners are compensated Q: What other features could a puzzle have? 1 Cryptocurrency Technologies Alternative Mining Puzzles On today’s menu . Alternative puzzle designs Used in practice, and speculative Variety of possible goals ASIC resistance, pool resistance, intrinsic benefits, etc. Essential security requirements Alternative Mining Puzzles • Essential Puzzle Requirements • ASIC-Resistant Puzzles • Proof-of-Useful-Work • Non-outsourceable Puzzles • Proof-of-Stake “Virtual Mining” 2 Cryptocurrency Technologies Alternative Mining Puzzles Puzzle Requirements A puzzle should ... – be cheap to verify – have adjustable difficulty – <other requirements> – have a chance of winning that is proportional to hashpower • Large player get only proportional advantage • Even small players get proportional compensation Bad Puzzle: a sequential Puzzle Consider a puzzle that takes N steps to solve a “Sequential” Proof of Work N Solution Found! 3 Cryptocurrency Technologies Alternative Mining Puzzles Bad Puzzle: a sequential Puzzle Problem: fastest miner always wins the race! Solution Found! Good Puzzle => Weighted Sample This property is sometimes called progress free. 4 Cryptocurrency Technologies Alternative Mining Puzzles Alternative Mining Puzzles • Essential Puzzle Requirements • ASIC-Resistant Puzzles • Proof-of-Useful-Work • Non-outsourceable Puzzles • Proof-of-Stake “Virtual Mining” ASIC Resistance – Why?! Goal: Ordinary people with idle laptops, PCs, or even mobile phones can mine! Lower barrier to entry! Approach: Reduce the gap between custom hardware and general purpose equipment. -
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. -
Coinbase Explores Crypto ETF (9/6) Coinbase Spoke to Asset Manager Blackrock About Creating a Crypto ETF, Business Insider Reports
Crypto Week in Review (9/1-9/7) Goldman Sachs CFO Denies Crypto Strategy Shift (9/6) GS CFO Marty Chavez addressed claims from an unsubstantiated report earlier this week that the firm may be delaying previous plans to open a crypto trading desk, calling the report “fake news”. Coinbase Explores Crypto ETF (9/6) Coinbase spoke to asset manager BlackRock about creating a crypto ETF, Business Insider reports. While the current status of the discussions is unclear, BlackRock is said to have “no interest in being a crypto fund issuer,” and SEC approval in the near term remains uncertain. Looking ahead, the Wednesday confirmation of Trump nominee Elad Roisman has the potential to tip the scales towards a more favorable cryptoasset approach. Twitter CEO Comments on Blockchain (9/5) Twitter CEO Jack Dorsey, speaking in a congressional hearing, indicated that blockchain technology could prove useful for “distributed trust and distributed enforcement.” The platform, given its struggles with how best to address fraud, harassment, and other misuse, could be a prime testing ground for decentralized identity solutions. Ripio Facilitates Peer-to-Peer Loans (9/5) Ripio began to facilitate blockchain powered peer-to-peer loans, available to wallet users in Argentina, Mexico, and Brazil. The loans, which utilize the Ripple Credit Network (RCN) token, are funded in RCN and dispensed to users in fiat through a network of local partners. Since all details of the loan and payments are recorded on the Ethereum blockchain, the solution could contribute to wider access to credit for the unbanked. IBM’s Payment Protocol Out of Beta (9/4) Blockchain World Wire, a global blockchain based payments network by IBM, is out of beta, CoinDesk reports. -
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. -
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.