Semantic and sensitivity aware location privacy protection for the internet of things
Berker Ağır, Jean-Paul Calbimonte, Karl Aberer · 2014
Abstract. Everyday applications and ubiquitous devices contribute data to the Internet of Things, oftentimes including sensitive information of people. This opens new challenges for protecting users ’ data from ad-versaries, who can perform different types of attacks using combinations of private and publicly available information. In this paper, we discuss some of the main challenges, especially regarding location-privacy, and a general approach for adaptively protecting this type of data. This ap-proach considers the semantics of the user location, as well as the user’s sensitivity preferences, and also builds an adversary model for estimating privacy levels. 1