PrivFramework: A System for Configurable and Automated Privacy Policy Compliance
This work addresses the problem of empowering data owners to specify and enforce their privacy preferences, which is a significant concern for individuals in the context of large-scale data collection and privacy risks.
This paper introduces PrivFramework, a system that allows data owners to define and enforce privacy policies on their data. It automatically checks Python analysis programs for compliance with these user-defined policies using static analysis.
Today's massive scale of data collection coupled with recent surges of consumer data leaks has led to increased attention towards data privacy and related risks. Conventional data privacy protection systems focus on reducing custodial risk and lack features empowering data owners. As an end user there are limited options available to specify and enforce one's own privacy preferences over their data. To address these concerns we present PrivFramework, a user-configurable frame-work for automated privacy policy compliance. PrivFramework allows data owners to write powerful privacy policies to protect their data and automatically enforces these policies against analysis programs written in Python. Using static-analysis PrivFramework automatically checks authorized analysis programs for compliance to user-defined policies.