Security without identification: transaction systems to make big brother obsolete
Communications of the ACM
Founding crytpography on oblivious transfer
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Protecting data privacy in private information retrieval schemes
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Communications of the ACM
ACM Computing Surveys (CSUR)
Untraceable electronic mail, return addresses, and digital pseudonyms
Communications of the ACM
Collaborative filtering with privacy via factor analysis
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
CLARISSE: A Machine Learning Tool to Initialize Student Models
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Replication is not needed: single database, computationally-private information retrieval
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
Privacy-preserving Distributed Clustering using Generative Models
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
State-of-the-art in privacy preserving data mining
ACM SIGMOD Record
Blind sales in electronic commerce
ICEC '04 Proceedings of the 6th international conference on Electronic commerce
SVD-based collaborative filtering with privacy
Proceedings of the 2005 ACM symposium on Applied computing
Fairplay—a secure two-party computation system
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
A formal treatment of onion routing
CRYPTO'05 Proceedings of the 25th annual international conference on Advances in Cryptology
ESORICS'05 Proceedings of the 10th European conference on Research in Computer Security
Journal of Computer Security
An agent-based approach for privacy-preserving recommender systems
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
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The use of recommender systems in e-commerce to guide customer choices presents a privacy protection problem that is twofold. We seek to protect the privacy interests of customers by trying to keep private their identity and demographic characteristics, and possibly also their buying preferences and behaviour. This can be desirable even if anonymity is used. Furthermore, we want to protect the commercial interests of the e-commerce service providers by allowing them to make recommendations as accurate as possible, without unnecessarily revealing valuable information they have legitimately accumulated, such as market trends, to third parties.In this paper, we concentrate on recommender systems based on demographic filtering, which make recommendations based on feedback of previous users of similar demographic characteristics (such as age, sex, level of education, wealth, geographical location, etc.). We propose a system called ALAMBIC, which adequately achieves the above privacy-protection objectives in this kind of recommender systems. Our system is based on a semi-trusted third party in which the users need only have limited confidence. A main originality of our approach is to split user data between that party and the service provider in such a way that neither can derive sensitive information from their share alone.