{"title":"Trusted Tamper-Evident Data Provenance","authors":"M. Taha, Sivadon Chaisiri, R. Ko","doi":"10.1109/Trustcom.2015.430","DOIUrl":null,"url":null,"abstract":"Data provenance, the origin and derivation history of data, is commonly used for security auditing, forensics and data analysis. While provenance loggers provide evidence of data changes, the integrity of the provenance logs is also critical for the integrity of the forensics process. However, to our best knowledge, few solutions are able to fully satisfy this trust requirement. In this paper, we propose a framework to enable tamper-evidence and preserve the confidentiality and integrity of data provenance using the Trusted Platform Module (TPM). Our framework also stores provenance logs in trusted and backup servers to guarantee the availability of data provenance. Tampered provenance logs can be discovered and consequently recovered by retrieving the original logs from the servers. Leveraging on TPM's technical capability, our framework guarantees data provenance collected to be admissible, complete, and confidential. More importantly, this framework can be applied to capture tampering evidence in large-scale cloud environments at system, network, and application granularities. We applied our framework to provide tamper-evidence for Progger, a cloud-based, kernel-space logger. Our results demonstrate the ability to conduct remote attestation of Progger logs' integrity, and uphold the completeness, confidential and admissible requirements.","PeriodicalId":277092,"journal":{"name":"2015 IEEE Trustcom/BigDataSE/ISPA","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Trustcom/BigDataSE/ISPA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Trustcom.2015.430","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
Data provenance, the origin and derivation history of data, is commonly used for security auditing, forensics and data analysis. While provenance loggers provide evidence of data changes, the integrity of the provenance logs is also critical for the integrity of the forensics process. However, to our best knowledge, few solutions are able to fully satisfy this trust requirement. In this paper, we propose a framework to enable tamper-evidence and preserve the confidentiality and integrity of data provenance using the Trusted Platform Module (TPM). Our framework also stores provenance logs in trusted and backup servers to guarantee the availability of data provenance. Tampered provenance logs can be discovered and consequently recovered by retrieving the original logs from the servers. Leveraging on TPM's technical capability, our framework guarantees data provenance collected to be admissible, complete, and confidential. More importantly, this framework can be applied to capture tampering evidence in large-scale cloud environments at system, network, and application granularities. We applied our framework to provide tamper-evidence for Progger, a cloud-based, kernel-space logger. Our results demonstrate the ability to conduct remote attestation of Progger logs' integrity, and uphold the completeness, confidential and admissible requirements.