The Decision Diffie-Hellman Problem
ANTS-III Proceedings of the Third International Symposium on Algorithmic Number Theory
Information sharing across private databases
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Foundations of Cryptography: Volume 2, Basic Applications
Foundations of Cryptography: Volume 2, Basic Applications
Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Privacy Preserving Data Mining (Advances in Information Security)
Privacy Preserving Data Mining (Advances in Information Security)
Privacy Preserving Nearest Neighbor Search
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Efficient Privacy-Preserving k-Nearest Neighbor Search
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
On private scalar product computation for privacy-preserving data mining
ICISC'04 Proceedings of the 7th international conference on Information Security and Cryptology
Privacy-preserving similarity measurement for access control policies
Proceedings of the 6th ACM workshop on Digital identity management
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k -Nearest Neighbor (k -NN) mining aims to retrieve the k most similar objects to the query objects. It can be incorporated into many data mining algorithms, such as outlier detection, clustering, and k -NN classification. Privacy-preserving distributedk -NN is developed to address the issue while preserving the participants' privacy. Several two-party privacy-preserving k -NN mining protocols on horizontally partitioned data had been proposed, but they fail to deal with the privacy issue when the number of the participating parties is greater than two. This paper proposes a set of protocols that can address the privacy issue when there are more than two participants. The protocols are devised with the probabilistic public-key cryptosystem and the communicative cryptosystem as the core privacy-preserving infrastructure. The protocols' security is proved based on the Secure Multi-party Computation theory.