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Prov-Trust: Towards a trustworthy sgx-based data provenance system

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Data provenance refers to records of the inputs, entities, systems, and processes that influence data of interest, providing a historical record of the data and its origins. Secure data provenance is vital to ensure accountability, forensics investigation of security attacks and privacy preservation. In this paper, we propose Prov-Trust, a decentralized and auditable SGX-based data provenance system relying on highly distributed ledgers. This consensually shared and synchronized database allows anchored data to have public witness, providing tamper-proof provenance data, enabling the transparency of data accountability, and enhancing the secrecy and availability of the provenance data. Prov-Trust relies on Intel SGX enclave to ensure a trusted execution of the provenance kernel to collect, store and query provenance records. The use of SGX enclave protects data provenance and users' credentials against malicious hosting and processing parties. Prov-Trust does not rely on a trusted third party to store provenance data while performing their verification using smart contracts and voting process. The storage of the provenance data in Prov-Trust is done using either the log events of Smart Contracts or blockchain's transactions depending on the provenance change event, which enables low storage costs. Finally, Prov-Trust ensures an accurate privacy-preserving auditing process based on blockchain traces and achieved thanks to events' logs that are signed by SGX enclaves, transactions being registered after each vote session, and sealing the linking information using encryption schemes.

Original languageEnglish
Title of host publicationICETE 2020 - Proceedings of the 17th International Joint Conference on e-Business and Telecommunications
EditorsChristian Callegari, Soon Xin Ng, Panagiotis Sarigiannidis, Sebastiano Battiato, Angel Serrano Sanchez de Leon, Adlen Ksentini, Pascal Lorenz, Mohammad Obaidat, Mohammad Obaidat, Mohammad Obaidat
PublisherSciTePress
Pages225-237
Number of pages13
ISBN (Electronic)9789897584459
DOIs
Publication statusPublished - 1 Jan 2020
Event17th International Conference on Security and Cryptography, SECRYPT 2020 - Part of the 17th International Joint Conference on e-Business and Telecommunications, ICETE 2020 - Virtual, Online, France
Duration: 8 Jul 202010 Jul 2020

Publication series

NameICETE 2020 - Proceedings of the 17th International Joint Conference on e-Business and Telecommunications
Volume3

Conference

Conference17th International Conference on Security and Cryptography, SECRYPT 2020 - Part of the 17th International Joint Conference on e-Business and Telecommunications, ICETE 2020
Country/TerritoryFrance
CityVirtual, Online
Period8/07/2010/07/20

Keywords

  • Blockchain
  • Data integrity
  • Data provenance
  • Intel sGX
  • Privacy preserving

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