Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
A maximum entropy approach to natural language processing
Computational Linguistics
Crowds: anonymity for Web transactions
ACM Transactions on Information and System Security (TISSEC)
Untraceable electronic mail, return addresses, and digital pseudonyms
Communications of the ACM
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
A new privacy model for hiding group interests while accessing the Web
Proceedings of the 2002 ACM workshop on Privacy in the Electronic Society
How Much Privacy? - A System to Safe Guard Personal Privacy while Releasing Databases
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Mixminion: Design of a Type III Anonymous Remailer Protocol
SP '03 Proceedings of the 2003 IEEE Symposium on Security and Privacy
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
PRAW—A PRivAcy model for the Web: Research Articles
Journal of the American Society for Information Science and Technology
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Privacy Protection: p-Sensitive k-Anonymity Property
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Specification of a framework for the anonymous use of privileges
Telematics and Informatics - Special issue: Developing a culture of privacy in the global village
Privacy-enhancing personalized web search
Proceedings of the 16th international conference on World Wide Web
Tor: the second-generation onion router
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
A Critique of k-Anonymity and Some of Its Enhancements
ARES '08 Proceedings of the 2008 Third International Conference on Availability, Reliability and Security
The cost of privacy: destruction of data-mining utility in anonymized data publishing
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
From t-Closeness to PRAM and Noise Addition Via Information Theory
PSD '08 Proceedings of the UNESCO Chair in data privacy international conference on Privacy in Statistical Databases
An Improved V-MDAV Algorithm for l-Diversity
ISIP '08 Proceedings of the 2008 International Symposiums on Information Processing
Enhanced P-Sensitive K-Anonymity Models for Privacy Preserving Data Publishing
Transactions on Data Privacy
Transferable Constant-Size Fair E-Cash
CANS '09 Proceedings of the 8th International Conference on Cryptology and Network Security
Personalized news recommendation based on click behavior
Proceedings of the 15th international conference on Intelligent user interfaces
Private location-based information retrieval through user collaboration
Computer Communications
Privacy preservation improvement by learning optimal profile generation rate
UM'03 Proceedings of the 9th international conference on User modeling
PET'02 Proceedings of the 2nd international conference on Privacy enhancing technologies
Content-based recommendation systems
The adaptive web
Optimized query forgery for private information retrieval
IEEE Transactions on Information Theory
A privacy-preserving architecture for the semantic web based on tag suppression
TrustBus'10 Proceedings of the 7th international conference on Trust, privacy and security in digital business
From t-Closeness-Like Privacy to Postrandomization via Information Theory
IEEE Transactions on Knowledge and Data Engineering
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part II
RePriv: Re-imagining Content Personalization and In-browser Privacy
SP '11 Proceedings of the 2011 IEEE Symposium on Security and Privacy
A game theoretic framework for data privacy preservation in recommender systems
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
Optimistic fair priced oblivious transfer
AFRICACRYPT'10 Proceedings of the Third international conference on Cryptology in Africa
Average divergence distance as a statistical discrimination measure for hidden Markov models
IEEE Transactions on Audio, Speech, and Language Processing
A privacy-protecting architecture for collaborative filtering via forgery and suppression of ratings
DPM'11 Proceedings of the 6th international conference, and 4th international conference on Data Privacy Management and Autonomous Spontaneus Security
Broadcast channels with confidential messages
IEEE Transactions on Information Theory
OB-PWS: Obfuscation-Based Private Web Search
SP '12 Proceedings of the 2012 IEEE Symposium on Security and Privacy
Query Profile Obfuscation by Means of Optimal Query Exchange between Users
IEEE Transactions on Dependable and Secure Computing
Optimal tag suppression for privacy protection in the semantic Web
Data & Knowledge Engineering
Privacy-Preserving Enhanced Collaborative Tagging
IEEE Transactions on Knowledge and Data Engineering
Future Generation Computer Systems
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Personalized information systems are information-filtering systems that endeavor to tailor information-exchange functionality to the specific interests of their users. The ability of these systems to profile users is, on the one hand, what enables such intelligent functionality, but on the other, the source of innumerable privacy risks. In this paper, we justify and interpret KL divergence as a criterion for quantifying the privacy of user profiles. Our criterion, which emerged from previous work in the domain of information retrieval, is here thoroughly examined by adopting the beautiful perspective of the method of types and large deviation theory, and under the assumption of two distinct adversary models. In particular, we first elaborate on the intimate connection between Jaynes' celebrated method of entropy maximization and the use of entropies and divergences as measures of privacy; and secondly, we interpret our privacy metric as false positives and negatives in a binary hypothesis testing.