Location Privacy in Pervasive Computing
IEEE Pervasive Computing
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ACM SIGMOBILE Mobile Computing and Communications Review
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In this paper we analyze a class of location disclosure in which location information from individuals is generated in an automated way, i.e. is observed by a ubiquitous infrastructure. Since such information is valuable for both scientific research and commercial use, location information might be passed on to third parties. Users are usually aware neither of the extent of the information disclosure (e.g. by carrying a mobile phone), nor how the collected data is used and by whom. In order to assess the expected privacy risk in terms of the possible extent of exposure, we propose an adversary model and a privacy metric that allow an evaluation of the possible privacy loss by using mobile communication infrastructure. Furthermore, a case study on the privacy effects of using GSM infrastructure was conducted with the goal of analyzing the side effects of using a mobile handset. Based on these results requirements for a privacy-aware mobile handheld device were derived.