Preserving Privacy of Agents in ParticipatorySensing Schemes for Traffic Estimation
Abstract
A measure of privacy infringement for agents (or participants) travelling across a transportation network in participatorysensing schemes for traffic estimation is introduced. The measure is defined to be the conditional probability that an external observer assigns to the private nodes in the transportation network, e.g., location of home or office, given all the position measurements that it broadcasts over time. An algorithm for finding an optimal tradeoff between the measure of privacy infringement and the expected estimation error, captured by the number of the nodes over which the participant stops broadcasting its position, is proposed. The algorithm searches over a family of policies in which an agent stops transmitting its position measurements if its distance (in terms of the number of hops) to the privacy sensitive node is smaller than a prescribed threshold. Employing such symmetric policies are advantageous in terms of the resources required for implementation and the ease of computation. The results are expanded to more general policies. Further, the effect of the heterogeneity of the population density on the optimal policy is explored. Finally, the relationship between the betweenness measure of centrality and the optimal privacypreserving policy of the agents is numerically explored.
 Publication:

arXiv eprints
 Pub Date:
 September 2016
 arXiv:
 arXiv:1609.01028
 Bibcode:
 2016arXiv160901028F
 Keywords:

 Mathematics  Optimization and Control;
 Computer Science  Systems and Control