Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
How to Explain Zero-Knowledge Protocols to Your Children
CRYPTO '89 Proceedings of the 9th Annual International Cryptology Conference on Advances in Cryptology
PEBL: positive example based learning for Web page classification using SVM
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Biometric Recognition: Security and Privacy Concerns
IEEE Security and Privacy
A tutorial on text-independent speaker verification
EURASIP Journal on Applied Signal Processing
An Efficient Protocol for Secure Two-Party Computation in the Presence of Malicious Adversaries
EUROCRYPT '07 Proceedings of the 26th annual international conference on Advances in Cryptology
An overview of text-independent speaker recognition: From features to supervectors
Speech Communication
Performance Comparison of Secure Comparison Protocols
DEXA '09 Proceedings of the 2009 20th International Workshop on Database and Expert Systems Application
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
Joint Factor Analysis Versus Eigenchannels in Speaker Recognition
IEEE Transactions on Audio, Speech, and Language Processing
A Framework for Secure Speech Recognition
IEEE Transactions on Audio, Speech, and Language Processing
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
A low overhead scaled equalized harmonic-based voice authentication system
Telematics and Informatics
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Speaker authentication systems require access to the voice of the user. A person's voice carries information about their gender, nationality etc., all of which become accessible to the system, which could abuse this knowledge. The system also stores users' voice prints --- these may be stolen and used to impersonate the users elsewhere. It is therefore important to develop privacy preserving voice authentication techniques that enable a system to authenticate users by their voice, while simultaneously obscuring the user's voice and voice patterns from the system. Prior work in this area has employed expensive cryptographic tools, or has cast authentication as a problem of exact match with compromised accuracy. In this paper we present a new technique that employs secure binary embeddings of feature vectors, to perform voice authentication in a privacy preserving manner with minimal computational overhead and little loss of classification accuracy.