2011 IEEE 27th International Conference on Data Engineering 2011
DOI: 10.1109/icde.2011.5767898
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MobiMix: Protecting location privacy with mix-zones over road networks

Abstract: Abstract-This paper presents MobiMix, a road network based mix-zone framework to protect location privacy of mobile users traveling on road networks. In contrast to spatial cloaking based location privacy protection, the approach in MobiMix is to break the continuity of location exposure by using mix-zones, where no applications can trace user movement. This paper makes two original contributions. First, we provide the formal analysis on the vulnerabilities of directly applying theoretical rectangle mix-zones … Show more

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Cited by 210 publications
(133 citation statements)
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“…Location privacy has been studied over the past decade along two orthogonal dimensions: spatial cloaking through location k-anonymity represented by [17,26,7,32,13,6] and mix-zone based privacy protection and its variations represented by [9,15,16,11,29,25]. However, these approaches are suitable only for snapshot queries and are inadequate and ineffective for protecting location privacy of mobile users with continuous query services.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Location privacy has been studied over the past decade along two orthogonal dimensions: spatial cloaking through location k-anonymity represented by [17,26,7,32,13,6] and mix-zone based privacy protection and its variations represented by [9,15,16,11,29,25]. However, these approaches are suitable only for snapshot queries and are inadequate and ineffective for protecting location privacy of mobile users with continuous query services.…”
Section: Related Workmentioning
confidence: 99%
“…Spatial cloaking is effective for snapshot queries but vulnerable to CQ-attacks. The second class of location anonymization techniques is represented by mix-zone development [9,15,16,11,29]. Mix-zones are spatial regions where a set of users enter, change pseudonyms in such a way that the mapping between their old and new pseudonyms is not revealed.…”
Section: Introductionmentioning
confidence: 99%
“…Various privacy protection algorithms proposed for data privacy have been adopted for protecting location privacy of mobile users. The types of privacy protection algorithms include anonymization [1,5,8,10,13,20], data suppression [18], trajectory inference prevention [2,3,[14][15][16] and encryption [11]. While most of the existing schemes are aimed at preventing the adversary from distinguishing the location of a given user from that of other users, their perturbation techniques are mostly unidirectional and lack the ability to de-anonymize the perturbed information even when a user accessing the information has suitable credentials for obtaining finer information.…”
Section: Related Workmentioning
confidence: 99%
“…It can be shown that, due to the nature of the data being exchanged between the user and the server, the frequent changing of the user"s name provides little protection for the user"s privacy. A more recent Investigation of the mix-zone approach has been applied to road networks [18]. They investigated the required number of users to satisfy the unlinkability property when there are repeated queries over an interval.…”
Section: Related Workmentioning
confidence: 99%