{"title":"UTXOAnalysis:基于UTXO的加密货币的分布式图存储和分析系统","authors":"Ruibin Yan, Zeyu Zhang , Dechun Yin, Zhihao Li, Yuan Gao, Yijun Gu","doi":"10.1016/j.compeleceng.2024.109760","DOIUrl":null,"url":null,"abstract":"<div><div>Relationship analysis of cryptocurrencies is crucial for understanding and regulating their ecosystems with graph structures. In particular, the relationships of the UTXO-based cryptocurrencies, which were developed earlier, form ecosystems with more integrated and larger graph structures. It is a challenge to efficiently store such large graphs and to efficiently query and analyze these graphs. In this paper, we propose UTXOAnalysis to solve these problems. UTXOAnalysis is a distributed graph storage and analysis system with a three-level structure. In the data collection framework, UTXOAnalysis adopts batch queries and block pruning. In the parsing and storage framework, UTXOAnalysis utilizes the parallel approaches of multi-graph parsing and storage. UTXOAnalysis also provides these methods for incremental data. In the analysis framework, UTXOAnalysis supplies address relationship analysis, transaction relationship analysis, and cryptocurrency flow tracing, which are the three basic analysis methods. In our experiments, we collected data from Bitcoin and Zcash to demonstrate the efficiency of data collection, parsing, storage, and basic analysis. UTXOAnalysis is more efficient in storing and analyzing UTXO-based cryptocurrencies than the baseline methods.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"120 ","pages":"Article 109760"},"PeriodicalIF":4.0000,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"UTXOAnalysis: A distributed graph storage and analysis system for UTXO-based cryptocurrencies\",\"authors\":\"Ruibin Yan, Zeyu Zhang , Dechun Yin, Zhihao Li, Yuan Gao, Yijun Gu\",\"doi\":\"10.1016/j.compeleceng.2024.109760\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Relationship analysis of cryptocurrencies is crucial for understanding and regulating their ecosystems with graph structures. In particular, the relationships of the UTXO-based cryptocurrencies, which were developed earlier, form ecosystems with more integrated and larger graph structures. It is a challenge to efficiently store such large graphs and to efficiently query and analyze these graphs. In this paper, we propose UTXOAnalysis to solve these problems. UTXOAnalysis is a distributed graph storage and analysis system with a three-level structure. In the data collection framework, UTXOAnalysis adopts batch queries and block pruning. In the parsing and storage framework, UTXOAnalysis utilizes the parallel approaches of multi-graph parsing and storage. UTXOAnalysis also provides these methods for incremental data. In the analysis framework, UTXOAnalysis supplies address relationship analysis, transaction relationship analysis, and cryptocurrency flow tracing, which are the three basic analysis methods. In our experiments, we collected data from Bitcoin and Zcash to demonstrate the efficiency of data collection, parsing, storage, and basic analysis. UTXOAnalysis is more efficient in storing and analyzing UTXO-based cryptocurrencies than the baseline methods.</div></div>\",\"PeriodicalId\":50630,\"journal\":{\"name\":\"Computers & Electrical Engineering\",\"volume\":\"120 \",\"pages\":\"Article 109760\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Electrical Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0045790624006876\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Electrical Engineering","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0045790624006876","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
UTXOAnalysis: A distributed graph storage and analysis system for UTXO-based cryptocurrencies
Relationship analysis of cryptocurrencies is crucial for understanding and regulating their ecosystems with graph structures. In particular, the relationships of the UTXO-based cryptocurrencies, which were developed earlier, form ecosystems with more integrated and larger graph structures. It is a challenge to efficiently store such large graphs and to efficiently query and analyze these graphs. In this paper, we propose UTXOAnalysis to solve these problems. UTXOAnalysis is a distributed graph storage and analysis system with a three-level structure. In the data collection framework, UTXOAnalysis adopts batch queries and block pruning. In the parsing and storage framework, UTXOAnalysis utilizes the parallel approaches of multi-graph parsing and storage. UTXOAnalysis also provides these methods for incremental data. In the analysis framework, UTXOAnalysis supplies address relationship analysis, transaction relationship analysis, and cryptocurrency flow tracing, which are the three basic analysis methods. In our experiments, we collected data from Bitcoin and Zcash to demonstrate the efficiency of data collection, parsing, storage, and basic analysis. UTXOAnalysis is more efficient in storing and analyzing UTXO-based cryptocurrencies than the baseline methods.
期刊介绍:
The impact of computers has nowhere been more revolutionary than in electrical engineering. The design, analysis, and operation of electrical and electronic systems are now dominated by computers, a transformation that has been motivated by the natural ease of interface between computers and electrical systems, and the promise of spectacular improvements in speed and efficiency.
Published since 1973, Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and electronic systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like signal and image processing, high-performance computing, parallel processing, and communications. Special attention will be paid to papers describing innovative architectures, algorithms, and software tools.