Multilayer feedforward networks are universal approximators
Neural Networks
Face recognition by elastic bunch graph matching
Intelligent biometric techniques in fingerprint and face recognition
A method for obtaining digital signatures and public-key cryptosystems
Communications of the ACM
High-Radix Montgomery Modular Exponentiation on Reconfigurable Hardware
IEEE Transactions on Computers
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Machine Learning
Handbook of Applied Cryptography
Handbook of Applied Cryptography
Fast Iris Detection for Personal Verification Using Modular Neural Nets
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
Automatic Fingerprint Verification Using Neural Networks
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Enhancing security and privacy in biometrics-based authentication systems
IBM Systems Journal - End-to-end security
Cancelable Biometric Filters for Face Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Support Vector Machines for Pattern Classification (Advances in Pattern Recognition)
Support Vector Machines for Pattern Classification (Advances in Pattern Recognition)
Designs, Codes and Cryptography
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
An analysis of BioHashing and its variants
Pattern Recognition
Remarks on BioHash and its mathematical foundation
Information Processing Letters
ARES '07 Proceedings of the The Second International Conference on Availability, Reliability and Security
Generating Cancelable Fingerprint Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Authentication of Individuals using Hand Geometry Biometrics: A Neural Network Approach
Neural Processing Letters
A survey of homomorphic encryption for nonspecialists
EURASIP Journal on Information Security
Oblivious neural network computing via homomorphic encryption
EURASIP Journal on Information Security
How to generate and exchange secrets
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
EURASIP Journal on Advances in Signal Processing
Fully homomorphic encryption using ideal lattices
Proceedings of the forty-first annual ACM symposium on Theory of computing
PalmHashing: a novel approach for cancelable biometrics
Information Processing Letters
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
Efficient privacy preserving k-means clustering
PAISI'10 Proceedings of the 2010 Pacific Asia conference on Intelligence and Security Informatics
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Concerns on widespread use of biometric authentication systems are primarily centered around template security, revocability, and privacy. The use of cryptographic primitives to bolster the authentication process can alleviate some of these concerns as shown by biometric cryptosystems. In this paper, we propose a provably secure and blind biometric authentication protocol, which addresses the concerns of user's privacy, template protection, and trust issues. The protocol is blind in the sense that it reveals only the identity, and no additional information about the user or the biometric to the authenticating server or vice-versa. As the protocol is based on asymmetric encryption of the biometric data, it captures the advantages of biometric authentication as well as the security of public key cryptography. The authentication protocol can run over public networks and provide nonrepudiable identity verification. The encryption also provides template protection, the ability to revoke enrolled templates, and alleviates the concerns on privacy in widespread use of biometrics. The proposed approach makes no restrictive assumptions on the biometric data and is hence applicable to multiple biometrics. Such a protocol has significant advantages over existing biometric cryptosystems, which use a biometric to secure a secret key, which in turn is used for authentication. We analyze the security of the protocol under various attack scenarios. Experimental results on four biometric datasets (face, iris, hand geometry, and fingerprint) show that carrying out the authentication in the encrypted domain does not affect the accuracy, while the encryption key acts as an additional layer of security.