Biblio

The ability to specify various policies with different overriding criteria allows for complex sets of sharing policies. This is particularly useful in situations in which data privacy depends on various properties of the data, and complex policies are needed to express the conditions under which data is protected. However, if overriding policy decisions constrain the affected data, decisions from overridden policies should not be suppressed completely, because they can still apply to subsets of the affected data. This article describes how a privacy policy framework can be extended with a mechanism to partially override decisions based on specified constraints. Our solution automatically generates complementary sets of decisions for both the overridden and the complementary, non-overridden subsets of the data, and thus, provides a means to specify a complex policies tailored to specific properties of the protected data.

This paper describes how a privacy policy framework can be extended with timing information to not only decide if requests for data are allowed at a given point in time, but also to decide for how long such permission is granted. Augmenting policy decisions with expiration information eliminates the need to reason about access permissions prior to every individual data access operation. This facilitates the application of privacy policy frameworks to protect multimedia streaming data where repeated re-computations of policy decisions are not a viable option. We show how timing information can be integrated into an existing declarative privacy policy framework. In particular, we discuss how to obtain valid expiration information in the presence of complex sets of policies with potentially interacting policies and varying timing information.

This article describes a privacy policy framework that can represent and reason about complex privacy policies. By using a Common Data Model together with a formal shareability theory, this framework enables the specification of expressive policies in a concise way without burdening the user with technical details of the underlying formalism. We also build a privacy policy decision engine that implements the framework and that has been deployed as the policy decision point in a novel enterprise privacy prototype system. Our policy decision engine supports two main uses: (1) interfacing with user interfaces for the creation, validation, and management of privacy policies; and (2) interfacing with systems that manage data requests and replies by coordinating privacy policy engine decisions and access to (encrypted) databases using various privacy enhancing technologies.