Provenance Threat Modeling
This work addresses security vulnerabilities in provenance systems, which are critical for data integrity and trust in various domains, but it appears incremental as it focuses on threat modeling and recommendations without introducing new methods.
The paper examines security risks in provenance systems, which track data history for applications like ownership attribution and quality assessment, and proposes security solutions to protect provenance information.
Provenance systems are used to capture history metadata, applications include ownership attribution and determining the quality of a particular data set. Provenance systems are also used for debugging, process improvement, understanding data proof of ownership, certification of validity, etc. The provenance of data includes information about the processes and source data that leads to the current representation. In this paper we study the security risks provenance systems might be exposed to and recommend security solutions to better protect the provenance information.