Secure smartcardbased fingerprint authentication

Clancy, T. Charles; Kiyavash, Negar; Lin, Dianliang

doi:10.1145/982507.982516

Cited by 403 publications

(336 citation statements)

References 14 publications

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“…Thus more chaff points provides better security, but arguably worse vault unlocking performance. The application of fuzzy vault to fingerprint identification appeared in the work of Clancy et al [9]. That paper showed realistic expectations on the numbers of chaff points and associated attack complexity.…”

Section: Previous Workmentioning

confidence: 98%

Symmetric hash functions for secure fingerprint biometric systems

Tulyakov

Farooq

Mansukhani

et al. 2007

Pattern Recognition Letters

102

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Securing biometrics databases from being compromised is one of the most important challenges that must be overcome in order to demonstrate the viability of biometrics based authentication. In this paper we present a novel method of hashing fingerprint minutia and performing fingerprint identification in the hash space. Our approach uses a family of symmetric hash functions and does not depend on the location of the (usually unstable) singular points (core and delta). In fact, most approaches of hashing minutia and developing a cancellable system described in the literature assume the location of the singular points. Others assume a pre-alignment between the test and the stored fingerprint templates. These assumptions are unrealistic given that fingerprints are very often only partially captured by the commercially available sensors. The Equal Error Rate (EER) achieved by our system is about 3%. We also present the performance analysis of a hybrid system that has an EER of about 2% which is very close to the performance of plain matching in the minutia space.

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Section: Previous Workmentioning

confidence: 98%

Symmetric hash functions for secure fingerprint biometric systems

Tulyakov

Farooq

Mansukhani

et al. 2007

Pattern Recognition Letters

102

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“…They give specific schemes that meet theoretical bounds for Hamming distance, set difference and edit distance respectively. Another distance measure, point-set difference, motivated from a popular representation for fingerprint features, is investigated in a number of studies [5,3,4]. A different approach [14,24,23] focuses on information leakage defined using Shannon entropy on continuous data with known distributions.…”

Section: Related Workmentioning

confidence: 99%

“…the number of sketches which non-zero probability of occurrences) is significantly smaller than 2 LP where L P is the length of the sketch and thus their sketches contain redundancy. One example is the chaff-based method [5] proposed to protect the biometric fingerprint. Here, a fingerprint is the secret x and can be represented as a set of 2D points.…”

Section: Redundancy In Sketchmentioning

confidence: 99%

“…Firstly, we found that when there are high redundancies in the sketch, more entropy could be lost compared with the straightforward method of handling the secrets independently. More precisely, the leftover entropy H ∞ (X, K|Q) may be less than H ∞ (X, K|P ), where P is simply the concatenation of the sketches for X and K. This observation is useful as a number of sketch constructions (e.g., [5]) would produce sketches that contain high redundancies but are difficult to compress. In the second observation, we give counter example to show that, when the randomness invested during sketch construction cannot be decoupled from the sketch, there are scenarios where the mixing is an redundant step as it does not provide more protection to the more important secret, i.e.…”

Section: Introductionmentioning

confidence: 99%

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Secure Sketch for Multiple Secrets

Fang

Chang

2010

Applied Cryptography and Network Security

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Abstract. Secure sketches are useful in extending cryptographic schemes to biometric data since they allow recovery of fuzzy secrets under inevitable noise. In practice, secrets derived from biometric data are seldom used alone, but typically employed in a multi-factor or a multimodality setting where multiple secrets with different roles and limitations are used together. To handle multiple secrets, we can generate a sketch for each secret independently and simply concatenate them. Alternatively, we can "mix" the secrets and individual sketches, for example, by taking the first secret as the key to encrypt the sketches of all other secrets. Hence, it is interesting to investigate how the secrets are to be mixed so as to cater for different requirements of individual secrets. We found that, by appropriate mixing, entropy loss on more important secrets (e.g., biometrics) can be "diverted" to less important ones (e.g., password or PIN), thus providing more protection to the former. On the other hand, we found that mixing may not be advisable if the amount of randomness invested in sketch construction is large, or the sketch contains high redundancy, or all secrets are of the same importance. Our analysis provides useful insights and guidelines in the applications of secure sketches in biometric systems.

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“…Currently, we use the x and y coordinates of minutiae points for locking/unlocking the vault (similar to the algorithms of Clancy et al [3], and Yang and Verbauwhede [21]). The encoding operation secures S with fingerprint minutiae data: if a query minutiae (that is aligned with respect to the template using the helper data as explained in Section 3) set that is similar to the template minutiae set is presented during decoding S can be reconstructed accurately.…”

Section: Encodingmentioning

confidence: 99%