Quantifying location privacy: the case of sporadic location exposure
PETS'11 Proceedings of the 11th international conference on Privacy enhancing technologies
Optimizing mixing in pervasive networks: a graph-theoretic perspective
ESORICS'11 Proceedings of the 16th European conference on Research in computer security
Cover locations: availing location-based services without revealing the location
Proceedings of the 10th annual ACM workshop on Privacy in the electronic society
Privacy and accountability for location-based aggregate statistics
Proceedings of the 18th ACM conference on Computer and communications security
Measuring query privacy in location-based services
Proceedings of the second ACM conference on Data and Application Security and Privacy
The impact of trace and adversary models on location privacy provided by K-anonymity
Proceedings of the First Workshop on Measurement, Privacy, and Mobility
Evaluating the privacy risk of location-based services
FC'11 Proceedings of the 15th international conference on Financial Cryptography and Data Security
Reasons, rewards, regrets: privacy considerations in location sharing as an interactive practice
Proceedings of the Eighth Symposium on Usable Privacy and Security
Protecting location privacy: optimal strategy against localization attacks
Proceedings of the 2012 ACM conference on Computer and communications security
Deanonymizing mobility traces: using social network as a side-channel
Proceedings of the 2012 ACM conference on Computer and communications security
On location privacy and quality of information in participatory sensing
Proceedings of the 8h ACM symposium on QoS and security for wireless and mobile networks
Exploring dependency for query privacy protection in location-based services
Proceedings of the third ACM conference on Data and application security and privacy
Combining social authentication and untrusted clouds for private location sharing
Proceedings of the 18th ACM symposium on Access control models and technologies
Secure cloud-assisted location based reminder
Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security
Enabling secure location-based services in mobile cloud computing
Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing
Addressing the concerns of the lacks family: quantification of kin genomic privacy
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
Geo-indistinguishability: differential privacy for location-based systems
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
Optimal sporadic location privacy preserving systems in presence of bandwidth constraints
Proceedings of the 12th ACM workshop on Workshop on privacy in the electronic society
Privacy vulnerability of published anonymous mobility traces
IEEE/ACM Transactions on Networking (TON)
A collaborative protocol for anonymous reporting in vehicular ad hoc networks
Computer Standards & Interfaces
Balancing authentication and location privacy in cooperative authentication
ANCS '13 Proceedings of the ninth ACM/IEEE symposium on Architectures for networking and communications systems
A classification of location privacy attacks and approaches
Personal and Ubiquitous Computing
Protecting query privacy in location-based services
Geoinformatica
Optimizing mix-zone coverage in pervasive wireless networks
Journal of Computer Security - Research in Computer Security and Privacy: Emerging Trends
Dynamic enforcement of knowledge-based security policies using probabilistic abstract interpretation
Journal of Computer Security
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It is a well-known fact that the progress of personal communication devices leads to serious concerns about privacy in general, and location privacy in particular. As a response to these issues, a number of Location-Privacy Protection Mechanisms (LPPMs) have been proposed during the last decade. However, their assessment and comparison remains problematic because of the absence of a systematic method to quantify them. In particular, the assumptions about the attacker's model tend to be incomplete, with the risk of a possibly wrong estimation of the users' location privacy. In this paper, we address these issues by providing a formal framework for the analysis of LPPMs, it captures, in particular, the prior information that might be available to the attacker, and various attacks that he can perform. The privacy of users and the success of the adversary in his location-inference attacks are two sides of the same coin. We revise location privacy by giving a simple, yet comprehensive, model to formulate all types of location-information disclosure attacks. Thus, by formalizing the adversary's performance, we propose and justify the right metric to quantify location privacy. We clarify the difference between three aspects of the adversary's inference attacks, namely their accuracy, certainty, and correctness. We show that correctness determines the privacy of users. In other words, the expected estimation error of the adversary is the metric of users' location privacy. We rely on well-established statistical methods to formalize and implement the attacks in a tool: the Location-Privacy Meter that measures the location privacy of mobile users, given various LPPMs. In addition to evaluating some example LPPMs, by using our tool, we assess the appropriateness of some popular metrics for location privacy: entropy and k-anonymity. The results show a lack of satisfactory correlation between these two metrics and the success of the adversary in inferring the users' actual locations.