{"title":"当差异隐私遇到查询控制:实用范围查询泄漏量化和缓解的混合框架","authors":"Xinyan Li;Yuefeng Du;Cong Wang","doi":"10.1109/TSC.2024.3517316","DOIUrl":null,"url":null,"abstract":"Encrypted range schemes are becoming increasingly attractive for commercial databases, as they allow for confidential query service on encrypted databases hosted on remote servers. These schemes, by design, leak specific patterns such as access, volume, and search patterns. However, they are vulnerable to leakage-abuse attacks (LAAs) that exploit these patterns to reconstruct the plaintext databases. In response, the query control paradigms have emerged, with our preceding framework, <italic>RangeQC</i>, being a notable example. These paradigms probe deeper into the intricacies of granular user query access control, advancing beyond past scheme-level efforts and acting as sentinels against the inadvertent leakage of delicate data patterns. While <italic>RangeQC</i> aimed to regulate high-leakage queries through query control, it encountered usability impediments. Acknowledging that query control alone might be insufficient, we introduce an additional layer of protection in our evolved framework, <italic>RangeQC+</i>. This fusion model combines query control with differential privacy-based data perturbation, a proactive strategy to muddle query responses and yield obfuscated leakage patterns. Complementing this approach, <italic>RangeQC+</i> incorporates refined, noise-resistant leakage metrics for accurate pattern analysis. Through comprehensive assessments and comparative analysis, <italic>RangeQC+</i> consistently showcases a balanced blend of enhanced performance, robust privacy, and user-friendly functionality.","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"18 2","pages":"1137-1151"},"PeriodicalIF":5.8000,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"When Differential Privacy Meets Query Control: A Hybrid Framework for Practical Range Query Leakage Quantification and Mitigation\",\"authors\":\"Xinyan Li;Yuefeng Du;Cong Wang\",\"doi\":\"10.1109/TSC.2024.3517316\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Encrypted range schemes are becoming increasingly attractive for commercial databases, as they allow for confidential query service on encrypted databases hosted on remote servers. These schemes, by design, leak specific patterns such as access, volume, and search patterns. However, they are vulnerable to leakage-abuse attacks (LAAs) that exploit these patterns to reconstruct the plaintext databases. In response, the query control paradigms have emerged, with our preceding framework, <italic>RangeQC</i>, being a notable example. These paradigms probe deeper into the intricacies of granular user query access control, advancing beyond past scheme-level efforts and acting as sentinels against the inadvertent leakage of delicate data patterns. While <italic>RangeQC</i> aimed to regulate high-leakage queries through query control, it encountered usability impediments. Acknowledging that query control alone might be insufficient, we introduce an additional layer of protection in our evolved framework, <italic>RangeQC+</i>. This fusion model combines query control with differential privacy-based data perturbation, a proactive strategy to muddle query responses and yield obfuscated leakage patterns. Complementing this approach, <italic>RangeQC+</i> incorporates refined, noise-resistant leakage metrics for accurate pattern analysis. Through comprehensive assessments and comparative analysis, <italic>RangeQC+</i> consistently showcases a balanced blend of enhanced performance, robust privacy, and user-friendly functionality.\",\"PeriodicalId\":13255,\"journal\":{\"name\":\"IEEE Transactions on Services Computing\",\"volume\":\"18 2\",\"pages\":\"1137-1151\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Services Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10797696/\",\"RegionNum\":2,\"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 Services Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10797696/","RegionNum":2,"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}
When Differential Privacy Meets Query Control: A Hybrid Framework for Practical Range Query Leakage Quantification and Mitigation
Encrypted range schemes are becoming increasingly attractive for commercial databases, as they allow for confidential query service on encrypted databases hosted on remote servers. These schemes, by design, leak specific patterns such as access, volume, and search patterns. However, they are vulnerable to leakage-abuse attacks (LAAs) that exploit these patterns to reconstruct the plaintext databases. In response, the query control paradigms have emerged, with our preceding framework, RangeQC, being a notable example. These paradigms probe deeper into the intricacies of granular user query access control, advancing beyond past scheme-level efforts and acting as sentinels against the inadvertent leakage of delicate data patterns. While RangeQC aimed to regulate high-leakage queries through query control, it encountered usability impediments. Acknowledging that query control alone might be insufficient, we introduce an additional layer of protection in our evolved framework, RangeQC+. This fusion model combines query control with differential privacy-based data perturbation, a proactive strategy to muddle query responses and yield obfuscated leakage patterns. Complementing this approach, RangeQC+ incorporates refined, noise-resistant leakage metrics for accurate pattern analysis. Through comprehensive assessments and comparative analysis, RangeQC+ consistently showcases a balanced blend of enhanced performance, robust privacy, and user-friendly functionality.
期刊介绍:
IEEE Transactions on Services Computing encompasses the computing and software aspects of the science and technology of services innovation research and development. It places emphasis on algorithmic, mathematical, statistical, and computational methods central to services computing. Topics covered include Service Oriented Architecture, Web Services, Business Process Integration, Solution Performance Management, and Services Operations and Management. The transactions address mathematical foundations, security, privacy, agreement, contract, discovery, negotiation, collaboration, and quality of service for web services. It also covers areas like composite web service creation, business and scientific applications, standards, utility models, business process modeling, integration, collaboration, and more in the realm of Services Computing.