Template 19599

Enrollment phase of Bioscrypt algorithm Soutar et al, Verification phase of Bioscrypt algorithm Soutar et al, Ratha et al. The method transforms the set of fingerprint minutiae from original space to another space using a one-way function. However, the performance of transformed template is lower than original template using the method.

The reason is that there is deviation of transformed minutiae position from expectation, and additional registration to transformation function can avoid the descend mentioned above, but the registration is difficult to control. Lee C et al. Actually, Tulyakov et al. They presented a method of hashing fingerprint minutia information and performing fingerprint identification in hashing space.

Due to the disorder of templates minutiae, input of hash function was not dependent on sequence i. They spread the concept of two factor authentication using key binding method. In order to enhance the security, they establish random relationship between a class of hash function and pair of minutiae structure by a particular user's key, so different user has different relationship between hash function and pair of minutiae structure.

The early theoretical research combined well-known techniques from the areas of error-correcting codes and cryptography to achieve a typical key binding scheme. Actually, this scheme derived from bit commitment scheme of cryptography, and follows the concept of commitment and witness and uses them for the inherently fuzzy biometric data. Fuzzy commitment scheme F has two sections: commitment and decommitment. In terms of commitment, F shall be constructed so as to commit an error-correcting codeword c using a witness x , where both c and x are n -bit strings.

In biometric scenarios, x typically represents a biometric template, such as a fingerprint. The codeword c represents a secret key protected under this template. Based on the fuzzy commitment scheme, Hao et al.

Compared to the fingerprint, iris is more suitable for the search of encryption because IrisCode is more canonical in coding. IrisCode has a fixed length of bit, together with some encryption algorithm to generate immediately, and the encryption and decryption is very easy to operate.

The most valued characteristic of the algorithm is linking the fuzziness of biometric with accuracy of cryptography perfectly.

She selects a polynomial p in a single variable x such that p encodes K in some way and computes the p A , projection of A lying on the polynomial p, thus form a finite point set A, p A. She then creates a number of random chaff points, with point set A, p A constitute the Vault. If B overlaps substantially with A, then B identifies many points in R that lie on polynomial p. Using error correction, he is able to reconstruct p exactly and thereby K.

If B does not overlap substantially with A, then it is infeasible for Bob to learn K , because of the presence of many chaff points. Based on the work of Juels et al, Clancy et al.

Being different from Juels et al, Clancy et al. Considering the decryption, using the nearest neighbor algorithm for extracted minutiae feature from matching fingerprint, search out the corresponding points in fingerprint vault, then take the points as input of RS correction code algorithm to compute the correct form of encrypted polynomials.

While like reference Davida et al, , the drawback is the corresponding pre-registration fingerprint image which the authors assume. Uludag et al. Nandakumar et al. So they propose the idea that add a password to the periphery of fuzzy vault system, and it is deformed minutiae parameter that are stored in new template but original data, where the deformed parameter is correlated to the user set-up password.

Encryption mechanism is independent on the security of fuzzy vault, so system is under double protection and attacker can take the legality user data only by breaching two systems in the one time.

Compared to ordinary fuzzy vault system, enhanced system has a higher rejection rate, but the cost is enhanced algorithm time complexity. Lee, Y proposes a new method of applying iris data to the fuzzy vault. The author obtains 16 bit length iris features by the methods of independent component analysis ICA -based feature extraction and K-means cluster pattern.

Zero FAR and about 0. Fuzzy Vault has become one of the most potential methods on biometric template protection technology. And apply each of these attacks on the Fuzzy Vault and biometric encryption system. Mihailescu proved that the system is vulnerable to the brute force attack and also gave several suggestions which can improve the fingerprint vault to a cryptographically secure algorithm by mathematic analysis.

Chang thought that genuine minutiae can be distinguished from chaff points by statistical characteristics of all points, actually chaff points tend to concentrate, they proved that the genuine minutiae can be found in much less searching time than force attack in the means of mathematic analysis and experimental validation.

All of these attack are based on the fact that the vault contain genuine minutiae data, in other words, there is definitely entropy loss. So, these attacks will have no entry point if those genuine minutiae are not stored in vault by some certain transformation. Dodis et al. Some certain information of secure sketch can be extracted from biometric signal by the operation that can tolerate error in a certain degree.

The published information can reconstruct original template perfectly while signal similar with original template is input. Meanwhile, the linchpin of the method is that the original template cannot be reconstructed by the republished information. Fuzzy extractor extracts approximate uniformly distributed random signal R from the input biometric signal, so R can be applied as a Key to all of the encryption.

In order to construct concrete algorithm for various biometric signal, Dodis et al. In the space of hamming distance, Dodis et al. In the space of set distance, they view fuzzy vault as approximate optimal secure sketch, and reform it into approximate optimal fuzzy extractor using same construction method. In the space of edit distance, they define the transformation from edit space to set space in order to transform optimal fuzzy extractor of set space into edit space.

Also, authors prove that the optimal secure sketch and fuzzy extractor can be constructed if entropy loss satisfies some certain condition. Literatures Dodis et al, ; Buhan et al, ; Boyen, ; Boyen et al, ; Li, Q et al, ; Sutcu, contribute to the study of key generation method. Literatures Tong et al, ; Arakala et al, extract robust key respectively from feature of fingercode and feature of minutiae structure, and progress attempt of practical algorithm.

Literature Zhang et al, actualizes iris-based fuzzy extractor, analyzes the influence on the performance of identification of difference between iris feature codes, and designs two layer cascade error-correcting scheme in which iterative codes and Reed-Solomon codes are applied. Khan et al. Encryption and data hiding techniques are used to improve the security and secrecy of the transmitted templates. Secret keys are generated by the biometric image and used as the parameter value and initial condition of chaotic map, and each transaction session has different secret keys to protect from the attacks.

Experimental results show that the security, performance, and accuracy of the presented scheme are encouraging comparable with other methods found in the current literature. Please try again after 30 seconds. Cannot use same password!

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