%0 Conference Paper %1 hasan09fast %A Hasan, Ragib %A Sion, Radu %A Winslett, Marianne %B Proceedings of the 7th USENIX Conference on File and Storage Technologies (FAST) %D 2009 %K fast my provenance security usenix %T The Case of the Fake Picasso: Preventing History Forgery with Secure Provenance

@inproceedings{hasan09fast, added-at = {2009-01-31T03:40:52.000+0100}, author = {Hasan, Ragib and Sion, Radu and Winslett, Marianne}, biburl = {https://www.bibsonomy.org/bibtex/2d2371cf294474ac5b3a866044c6a0721/ragibhasan}, booktitle = {Proceedings of the 7th USENIX Conference on File and Storage Technologies (FAST)}, description = {As increasing amounts of valuable information are produced and persist digitally, the ability to determine the origin of data becomes important. In science, medicine, commerce, and government, data provenance tracking is essential for rights protection, regulatory compliance, management of intelligence and medical data, and authentication of information as it flows through workplace tasks. While significant research has been conducted in this area, the associated security and privacy issues have not been explored, leaving provenance information vulnerable to illicit alteration as it passes through untrusted environments. In this talk, we show how to provide strong integrity and confidentiality assurances for data provenance information in an untrusted distributed environment. We describe our provenance-aware system prototype that implements provenance tracking of data writes at the application layer, which makes it extremely easy to deploy. We present empirical results that show that, for typical real-life workloads, the run-time overhead of our approach to recording provenance with confidentiality and integrity guarantees ranges from 1% - 13%.}, interhash = {7c343c9ef32355b46dcc3bf65e4d7cd5}, intrahash = {d2371cf294474ac5b3a866044c6a0721}, keywords = {fast my provenance security usenix}, location = {San Francisco, CA}, note = {As increasing amounts of valuable information are produced and persist digitally, the ability to determine the origin of data becomes important. In science, medicine, commerce, and government, data provenance tracking is essential for rights protection, regulatory compliance, management of intelligence and medical data, and authentication of information as it flows through workplace tasks. While significant research has been conducted in this area, the associated security and privacy issues have not been explored, leaving provenance information vulnerable to illicit alteration as it passes through untrusted environments. In this talk, we show how to provide strong integrity and confidentiality assurances for data provenance information in an untrusted distributed environment. We describe our provenance-aware system prototype that implements provenance tracking of data writes at the application layer, which makes it extremely easy to deploy. We present empirical results that show that, for typical real-life workloads, the run-time overhead of our approach to recording provenance with confidentiality and integrity guarantees ranges from 1% - 13%.}, timestamp = {2009-01-31T20:48:51.000+0100}, title = {The Case of the Fake Picasso: Preventing History Forgery with Secure Provenance}, year = 2009 }