CCS '99 Proceedings of the 6th ACM conference on Computer and communications security
Cryptographic Key Generation from Voice
SP '01 Proceedings of the 2001 IEEE Symposium on Security and Privacy
Secure smartcardbased fingerprint authentication
WBMA '03 Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications
A secure biometric authentication scheme based on robust hashing
MM&Sec '05 Proceedings of the 7th workshop on Multimedia and security
Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data
SIAM Journal on Computing
New shielding functions to enhance privacy and prevent misuse of biometric templates
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Hiding secret points amidst chaff
EUROCRYPT'06 Proceedings of the 24th annual international conference on The Theory and Applications of Cryptographic Techniques
Approximate image message authentication codes
IEEE Transactions on Multimedia
IEEE Transactions on Information Theory
EURASIP Journal on Advances in Signal Processing
An application of the Goldwasser-Micali cryptosystem to biometric authentication
ACISP'07 Proceedings of the 12th Australasian conference on Information security and privacy
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In order to apply cryptographic operations on noisy data, a recent approach employs some additional public data, known as secure sketch, to correct the noise so that consistent outcome can be obtained. This approach can be employed to extract authentication tags from noisy multimedia or biometric objects, by including the sketch in the tags. However, there are a few issues that need to be addressed. Firstly, those objects are typically represented in a continuous domain, and hence further quantization is required in order to obtain a short authentication tag. Secondly, for the purpose of authentication, forgery and preimage attacks are major concerns. However, such attacks are not considered in the notion of secure sketch. To handle the first issue, we give a construction using two levels of quantization. The second issue leads to the proposed additional requirement on sensitivity. We study how to choose the optimal parameters under the trade-off of robustness, size and sensitivity, and show that in many practical settings, the two-level quantization can be significantly more effective than a seemingly natural method of assigning one bit to each coefficient.