Privacy-preserving fingercode authentication
Proceedings of the 12th ACM workshop on Multimedia and security
Efficient privacy-preserving face recognition
ICISC'09 Proceedings of the 12th international conference on Information security and cryptology
Product Quantization for Nearest Neighbor Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Universal Rate-Efficient Scalar Quantization
IEEE Transactions on Information Theory
Secure binary embeddings for privacy preserving nearest neighbors
WIFS '11 Proceedings of the 2011 IEEE International Workshop on Information Forensics and Security
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This paper presents a moderately secure but very efficient approximate nearest neighbors search. After detailing the threats pertaining to the `honest but curious' model, our approach starts from a state-of-the-art algorithm in the domain of approximate nearest neighbors search. We gradually develop mechanisms partially blocking the attacks threatening the original algorithm. The loss of performances compared to the original algorithm is mainly an overhead of a constant computation time and communication payload which are independent of the size of the database.