{"title":"可检索性的一般有效动态证明","authors":"Mohammad Etemad, Alptekin Küpçü","doi":"10.1145/2996429.2996439","DOIUrl":null,"url":null,"abstract":"Together with its great advantages, cloud storage brought many interesting security issues to our attention. Since 2007, with the first efficient storage integrity protocols Proofs of Retrievability (PoR) of Juels and Kaliski, and Provable Data Possession (PDP) of Ateniese et al., many researchers worked on such protocols. The difference among PDP and PoR models were greatly debated. The first DPDP scheme was shown by Erway et al. in 2009, while the first DPoR scheme was created by Cash et al. in 2013. We show how to obtain DPoR from DPDP, PDP, and erasure codes, making us realize that even though we did not know it, we could have had a DPoR solution in 2009. We propose a general framework for constructing DPoR schemes that encapsulates known DPoR schemes as its special cases. We show practical and interesting optimizations enabling better performance than Chandran et al. and Shi et al. constructions. For the first time, we show how to obtain constant audit bandwidth for DPoR, independent of the data size, and how the client can greatly speed up updates with O(λ√n) local storage (where n is the number of blocks, and λ is the security parameter), which corresponds to ~ 3MB for 10GB outsourced data, and can easily be obtained in today's smart phones, let alone computers.","PeriodicalId":373063,"journal":{"name":"Proceedings of the 2016 ACM on Cloud Computing Security Workshop","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Generic Efficient Dynamic Proofs of Retrievability\",\"authors\":\"Mohammad Etemad, Alptekin Küpçü\",\"doi\":\"10.1145/2996429.2996439\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Together with its great advantages, cloud storage brought many interesting security issues to our attention. Since 2007, with the first efficient storage integrity protocols Proofs of Retrievability (PoR) of Juels and Kaliski, and Provable Data Possession (PDP) of Ateniese et al., many researchers worked on such protocols. The difference among PDP and PoR models were greatly debated. The first DPDP scheme was shown by Erway et al. in 2009, while the first DPoR scheme was created by Cash et al. in 2013. We show how to obtain DPoR from DPDP, PDP, and erasure codes, making us realize that even though we did not know it, we could have had a DPoR solution in 2009. We propose a general framework for constructing DPoR schemes that encapsulates known DPoR schemes as its special cases. We show practical and interesting optimizations enabling better performance than Chandran et al. and Shi et al. constructions. For the first time, we show how to obtain constant audit bandwidth for DPoR, independent of the data size, and how the client can greatly speed up updates with O(λ√n) local storage (where n is the number of blocks, and λ is the security parameter), which corresponds to ~ 3MB for 10GB outsourced data, and can easily be obtained in today's smart phones, let alone computers.\",\"PeriodicalId\":373063,\"journal\":{\"name\":\"Proceedings of the 2016 ACM on Cloud Computing Security Workshop\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2016 ACM on Cloud Computing Security Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2996429.2996439\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 ACM on Cloud Computing Security Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2996429.2996439","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
摘要
云存储具有巨大的优势,同时也给我们带来了许多有趣的安全问题。自2007年以来,随着Juels和Kaliski的第一个高效存储完整性协议proof of Retrievability (PoR)和Ateniese等人的可证明数据占有(PDP),许多研究人员开始研究这类协议。PDP和PoR模型之间的差异存在很大的争议。第一个DPDP方案由Erway等人于2009年提出,第一个DPDP方案由Cash等人于2013年提出。我们展示了如何从DPDP、PDP和擦除码中获得DPoR,使我们意识到,即使我们不知道,我们也可以在2009年有一个DPoR解决方案。我们提出了一个构建DPoR方案的通用框架,该框架将已知的DPoR方案封装为其特殊情况。我们展示了实用和有趣的优化,使性能优于Chandran等人和Shi等人的结构。我们首次展示了如何为dpr获得独立于数据大小的恒定审计带宽,以及客户端如何使用O(λ√n)本地存储(其中n是块数,λ是安全参数)大大加快更新速度,这相当于10GB外包数据的~ 3MB,并且可以很容易地在今天的智能手机中获得,更不用说计算机了。
Generic Efficient Dynamic Proofs of Retrievability
Together with its great advantages, cloud storage brought many interesting security issues to our attention. Since 2007, with the first efficient storage integrity protocols Proofs of Retrievability (PoR) of Juels and Kaliski, and Provable Data Possession (PDP) of Ateniese et al., many researchers worked on such protocols. The difference among PDP and PoR models were greatly debated. The first DPDP scheme was shown by Erway et al. in 2009, while the first DPoR scheme was created by Cash et al. in 2013. We show how to obtain DPoR from DPDP, PDP, and erasure codes, making us realize that even though we did not know it, we could have had a DPoR solution in 2009. We propose a general framework for constructing DPoR schemes that encapsulates known DPoR schemes as its special cases. We show practical and interesting optimizations enabling better performance than Chandran et al. and Shi et al. constructions. For the first time, we show how to obtain constant audit bandwidth for DPoR, independent of the data size, and how the client can greatly speed up updates with O(λ√n) local storage (where n is the number of blocks, and λ is the security parameter), which corresponds to ~ 3MB for 10GB outsourced data, and can easily be obtained in today's smart phones, let alone computers.