Computer Science Department
School of Computer Science, Carnegie Mellon University


Purpose Restrictions on Information Use

Michael Carl Tschantz, Anupam Datta, Jeannette M. Wing

June 2013


Keywords: Privacy, Formal Methods, Audit, Partially Observable Markov Decision Processes

Privacy policies in sectors as diverse as Web services, finance and healthcare often place restrictions on the purposes for which a governed entity may use personal information. Thus, automated methods for enforcing privacy policies require a semantics of purpose restrictions to determine whether a governed agent used information for a purpose. We provide such a semantics using a formalism based on planning. We model planning using Partially Observable Markov Decision Processes (POMDPs), which supports an explicit model of information. We argue that information use is for a purpose if and only if the information is used while planning to optimize the satisfaction of that purpose under the POMDP model. We determine information use by simulating ignorance of the information prohibited by the purpose restriction, which we relate to noninterference. We use this semantics to develop a sound audit algorithm to automate the enforcement of purpose restrictions.

21 pages

Also appears as CyLab Technical Report CMU-CyLab-13-005

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