2016/09/05 by Farhad Farokhi, Iman Shames, Farokhi, Farhad +1 · 1 citation
Computer Science · Social Sciences · #FOS: Electrical engineering #FOS: Mathematics #Mobile Crowdsensing and Crowdsourcing #Optimization and Control (math.OC) #Privacy-Preserving Technologies in Data #Systems and Control (eess.SY) #Transportation Planning and Optimization #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1609.01028
openalex publication_date 2016/09/05 · openalex created_date 2022/08/20 · openalex updated_date 2026/07/28
A measure of privacy infringement for agents (or participants) travelling\nacross a transportation network in participatory-sensing schemes for traffic\nestimation is introduced. The measure is defined to be the conditional\nprobability that an external observer assigns to the private nodes in the\ntransportation network, e.g., location of home or office, given all the\nposition measurements that it broadcasts over time. An algorithm for finding an\noptimal trade-off between the measure of privacy infringement and the expected\nestimation error, captured by the number of the nodes over which the\nparticipant stops broadcasting its position, is proposed. The algorithm\nsearches over a family of policies in which an agent stops transmitting its\nposition measurements if its distance (in terms of the number of hops) to the\nprivacy sensitive node is smaller than a prescribed threshold. Employing such\nsymmetric policies are advantageous in terms of the resources required for\nimplementation and the ease of computation. The results are expanded to more\ngeneral policies. Further, the effect of the heterogeneity of the population\ndensity on the optimal policy is explored. Finally, the relationship between\nthe betweenness measure of centrality and the optimal privacy-preserving policy\nof the agents is numerically explored.\n