Enhanced Accuracy Moment Invariants for Biometric Recognition and Cryptosystems
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Securing medical records on smart phones
Proceedings of the first ACM workshop on Security and privacy in medical and home-care systems
A secure cryptosystem from palm vein biometrics
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
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Existing asymmetric encryption algorithms require the storage of the secret private key. Stored keys are often protected by poorly selected user passwords that can either be guessed or obtained through brute force attacks. This is a weak link in the overall encryption system and can potentially compromise the integrity of sensitive data. Combining biometrics with cryptography is seen as a possible solution but any biometric cryptosystem must be able to overcome small variations present between different acquisitions of the same biometric in order to produce consistent keys. This paper discusses a new method which uses an entropy based feature extraction process coupled with Reed-Solomon error correcting codes that can generate deterministic bit-sequences from the output of an iterative one-way transform. The technique is evaluated using 3D face data and is shown to reliably produce keys of suitable length for 128-bit Advanced Encryption Standard (AES).