Scalable privacy
Joshua Joy, Dylan Gray, Ciarán McGoldrick, Mário Gerla · 2017
Given that the exact answer to a question is fixed, we ask is it possible to strengthen the privacy by increasing the crowd size that participates even though they do not contribute to the exact answer? In this paper, we introduce the notion of scalable privacy whereby data owners not at a particular location privatize their response such that they respond as if they are at a location (even when they are not). Immediately the question of utility is raised and we examine the tradeoffs to construct such a privacy mechanism so that it scales in both privacy and utility.