Anis Yousefi - Network Security Center, Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
Rasool Jalili - Network Security Center, Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
Mahdi Niamanesh - Network Security Center, Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

One of the most challenging problems of pervasive computing is protecting the privacy of individuals' data by respecting the principles of awareness and consent with minimum distraction. A suitable approach should consider the intention of all authorized entities determining data disclosure and usage regulations. Therefore, as an extension to current privacy protection approaches which consider only one determiner for a private data item, we propose the idea of multi-determiner privacy protection. In this paper, we investigate possible determiners of private data and propose a set of meta-data which are required to cover the concept of multideterminacy including ownership-information, operators, and DELEGATION behavior. Besides, we devise and evaluate a deadlock-free and conflict-free algorithm to manage ownership and DELEGATION scenario in answering a request. We subsequently integrate the algorithm and the required meta-data in a multi-determiner privacy protection architecture which works as a mediator to protect multi-determiner private data. We demonstrate the applicability of our work through a prototype implementation and realization of a sample scenario.

Data Privacy, Pervasive Computing, Multi-Determiner Private Data, Privacy Protection System