{"title":"负责任的分散ttp和激励机制的元宇宙数据交换","authors":"Liang Zhang;Xingyu Wu;Yuhang Ma;Haibin Kan","doi":"10.1109/TBDATA.2025.3533924","DOIUrl":null,"url":null,"abstract":"As a global virtual environment, the metaverse poses various challenges regarding data storage, sharing, interoperability, and privacy preservation. Typically, a trusted third party (TTP) is considered necessary in these scenarios. However, relying on a single TTP may introduce biases, compromise privacy, or lead to single-point-of-failure problem. To address these challenges and enable secure data exchange in the metaverse, we propose a system based on decentralized TTPs and the Ethereum blockchain. First, we use the threshold ElGamal cryptosystem to create the decentralized TTPs, employing verifiable secret sharing (VSS) to force owners to share data honestly. Second, we leverage the Ethereum blockchain to serve as the public communication channel, automatic verification machine, and smart contract engine. Third, we apply discrete logarithm equality (DLEQ) algorithms to generate non-interactive zero knowledge (NIZK) proofs when encrypted data is uploaded to the blockchain. Fourth, we present an incentive mechanism to benefit data owners and TTPs from data-sharing activities, as well as a penalty policy if malicious behavior is detected. Consequently, we construct a data exchange framework for the metaverse, in which all involved entities are accountable. Finally, we perform comprehensive experiments to demonstrate the feasibility and analyze the properties of the proposed system.","PeriodicalId":13106,"journal":{"name":"IEEE Transactions on Big Data","volume":"11 5","pages":"2431-2442"},"PeriodicalIF":5.7000,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data Exchange for the Metaverse With Accountable Decentralized TTPs and Incentive Mechanisms\",\"authors\":\"Liang Zhang;Xingyu Wu;Yuhang Ma;Haibin Kan\",\"doi\":\"10.1109/TBDATA.2025.3533924\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As a global virtual environment, the metaverse poses various challenges regarding data storage, sharing, interoperability, and privacy preservation. Typically, a trusted third party (TTP) is considered necessary in these scenarios. However, relying on a single TTP may introduce biases, compromise privacy, or lead to single-point-of-failure problem. To address these challenges and enable secure data exchange in the metaverse, we propose a system based on decentralized TTPs and the Ethereum blockchain. First, we use the threshold ElGamal cryptosystem to create the decentralized TTPs, employing verifiable secret sharing (VSS) to force owners to share data honestly. Second, we leverage the Ethereum blockchain to serve as the public communication channel, automatic verification machine, and smart contract engine. Third, we apply discrete logarithm equality (DLEQ) algorithms to generate non-interactive zero knowledge (NIZK) proofs when encrypted data is uploaded to the blockchain. Fourth, we present an incentive mechanism to benefit data owners and TTPs from data-sharing activities, as well as a penalty policy if malicious behavior is detected. Consequently, we construct a data exchange framework for the metaverse, in which all involved entities are accountable. Finally, we perform comprehensive experiments to demonstrate the feasibility and analyze the properties of the proposed system.\",\"PeriodicalId\":13106,\"journal\":{\"name\":\"IEEE Transactions on Big Data\",\"volume\":\"11 5\",\"pages\":\"2431-2442\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-01-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Big Data\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10854874/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Big Data","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10854874/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Data Exchange for the Metaverse With Accountable Decentralized TTPs and Incentive Mechanisms
As a global virtual environment, the metaverse poses various challenges regarding data storage, sharing, interoperability, and privacy preservation. Typically, a trusted third party (TTP) is considered necessary in these scenarios. However, relying on a single TTP may introduce biases, compromise privacy, or lead to single-point-of-failure problem. To address these challenges and enable secure data exchange in the metaverse, we propose a system based on decentralized TTPs and the Ethereum blockchain. First, we use the threshold ElGamal cryptosystem to create the decentralized TTPs, employing verifiable secret sharing (VSS) to force owners to share data honestly. Second, we leverage the Ethereum blockchain to serve as the public communication channel, automatic verification machine, and smart contract engine. Third, we apply discrete logarithm equality (DLEQ) algorithms to generate non-interactive zero knowledge (NIZK) proofs when encrypted data is uploaded to the blockchain. Fourth, we present an incentive mechanism to benefit data owners and TTPs from data-sharing activities, as well as a penalty policy if malicious behavior is detected. Consequently, we construct a data exchange framework for the metaverse, in which all involved entities are accountable. Finally, we perform comprehensive experiments to demonstrate the feasibility and analyze the properties of the proposed system.
期刊介绍:
The IEEE Transactions on Big Data publishes peer-reviewed articles focusing on big data. These articles present innovative research ideas and application results across disciplines, including novel theories, algorithms, and applications. Research areas cover a wide range, such as big data analytics, visualization, curation, management, semantics, infrastructure, standards, performance analysis, intelligence extraction, scientific discovery, security, privacy, and legal issues specific to big data. The journal also prioritizes applications of big data in fields generating massive datasets.