Indoor Location Based Services. Despite their widespread adoption, location-based services (LBS) are heavily limited in indoor spaces. This is due to several factors: GPS does not work out of the box, different kind of positioning technologies are available, the movement is subject to more constraints, elevation is more significant w.r.t. outdoor due to overlapping subspaces. As a consequence even well studied problems, such as spatial queries, need to be reformulated to cover this evolving scenario. We plan to investigate all aspect of LBS in interior spaces, ranging from data collection and privacy protection to data management and analytics.
Privacy in Location Based Services. The widespread adoption of location-based services (LBS) raises increasing concerns for the protection of personal location information. A common strategy, referred to as obfuscation (or cloaking), to protect location privacy is based on forwarding the LBS provider a coarse user location instead of the actual user location. Conventional approaches are unable to guarantee privacy when the adversary is aware of the geographical context, in particular of the semantic locations and the statistical distribution of positions in the given space. We aim at elaborating on the privacy model and architectural framework we already proposed for personalized cloaking of semantic locations. Collaborations: Università degli Studi di Milano, TOBB University of Economics and Technology (Ankara), CERIAS (Center for Education and Research in Information Assurance and Security) at Purdue University.
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