الفهرس 
Data provenance
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Abstract
As the number of provenance aware organizations increases, particularly in workflow scientific domains, sharing provenance data becomes a necessity. Current workflow provenance sanitization approaches do not address the disclosure problem of sensitive information through inferences. Consequently, the first part of this thesis, introduces a workflow provenance sanitization approach that maximize both graph utility and privacy with respect to the influences of various workflow constraints. The second part of this thesis introduces a Workflow Delegation Model (WFDM) that utilizes provenance and workflow constraints to prevent malicious delegatee from attacking workflow privacy as well as extending the delegation functionalities. A comprehensive security framework that integrates the aforementioned techniques is presented in this thesis