B. Malin, E. Airoldi, Samuel Edoho-Eket, Yiheng Li
{"title":"Configurable security protocols for multi-party data analysis with malicious participants","authors":"B. Malin, E. Airoldi, Samuel Edoho-Eket, Yiheng Li","doi":"10.1109/ICDE.2005.37","DOIUrl":null,"url":null,"abstract":"Standard multi-party computation models assume semi-honest behavior, where the majority of participants implement protocols according to specification, an assumption not always plausible. In this paper we introduce a multi-party protocol for collaborative data analysis when participants are malicious and fail to follow specification. The protocol incorporates a semi-trusted third party, which analyzes encrypted data and provides honest responses that only intended recipients can successfully decrypt. The protocol incorporates data confidentiality by enabling participants to receive encrypted responses tailored to their own encrypted data submissions without revealing plaintext to other participants, including the third party. As opposed to previous models, trust need only be placed on a single participant with no data at stake. Additionally, the proposed protocol is configurable in a way that security features are controlled by independent subprotocols. Various combinations of subprotocols allow for a flexible security system, appropriate for a number of distributed data applications, such as secure list comparison.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"21st International Conference on Data Engineering (ICDE'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2005.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
Standard multi-party computation models assume semi-honest behavior, where the majority of participants implement protocols according to specification, an assumption not always plausible. In this paper we introduce a multi-party protocol for collaborative data analysis when participants are malicious and fail to follow specification. The protocol incorporates a semi-trusted third party, which analyzes encrypted data and provides honest responses that only intended recipients can successfully decrypt. The protocol incorporates data confidentiality by enabling participants to receive encrypted responses tailored to their own encrypted data submissions without revealing plaintext to other participants, including the third party. As opposed to previous models, trust need only be placed on a single participant with no data at stake. Additionally, the proposed protocol is configurable in a way that security features are controlled by independent subprotocols. Various combinations of subprotocols allow for a flexible security system, appropriate for a number of distributed data applications, such as secure list comparison.