Algorithms for clustering data
Algorithms for clustering data
The dining cryptographers problem: unconditional sender and recipient untraceability
Journal of Cryptology
Computers and Industrial Engineering
Mix Zones: User Privacy in Location-aware Services
PERCOMW '04 Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops
A Mathematical Theory of Communication
A Mathematical Theory of Communication
Introduction to Clustering Large and High-Dimensional Data
Introduction to Clustering Large and High-Dimensional Data
k-Unlinkability: A privacy protection model for distributed data
Data & Knowledge Engineering
Towards an information theoretic metric for anonymity
PET'02 Proceedings of the 2nd international conference on Privacy enhancing technologies
Attacking unlinkability: the importance of context
PET'07 Proceedings of the 7th international conference on Privacy enhancing technologies
On the effectiveness of changing pseudonyms to provide location privacy in VANETS
ESAS'07 Proceedings of the 4th European conference on Security and privacy in ad-hoc and sensor networks
AMOEBA: Robust Location Privacy Scheme for VANET
IEEE Journal on Selected Areas in Communications
A distortion-based metric for location privacy
Proceedings of the 8th ACM workshop on Privacy in the electronic society
A location privacy metric for V2X communication systems
SARNOFF'09 Proceedings of the 32nd international conference on Sarnoff symposium
Measuring long-term location privacy in vehicular communication systems
Computer Communications
Evaluating adversarial partitions
ESORICS'10 Proceedings of the 15th European conference on Research in computer security
Relations among privacy notions
ACM Transactions on Information and System Security (TISSEC)
Privacy-preserving smart metering with multiple data Consumers
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Unlinkability describes the inability of an observer to decide whether certain items of interest are related or not. Privacy aware protocol designers need a consistent and meaningful unlinkability measure to asses protocols in face of different attacks. In this paper we show that entropy measures are not sufficient for measuring unlinkability. We propose an alternative measure that estimates the error made by an attacker. We show by example that our expected distance provides a consistent measure that offers a better estimation of message-unlinkability.