THRIVE: Threshold Homomorphic encryption based secure and privacy preserving bIometric VErification system

In this paper, we propose a new biometric verification and template protection system which we call the THRIVE system. The system includes novel enrollment and authentication protocols based on threshold homomorphic cryptosystem where the private key is shared between a user and the verifier. In the THRIVE system, only encrypted binary biometric templates are stored in the database and verification is performed via homomorphically randomized templates, thus, original templates are never revealed during the authentication stage. The THRIVE system is designed for the malicious model where the cheating party may arbitrarily deviate from the protocol specification. Since threshold homomorphic encryption scheme is used, a malicious database owner cannot perform decryption on encrypted templates of the users in the database. Therefore, security of the THRIVE system is enhanced using a two-factor authentication scheme involving the user's private key and the biometric data. We prove security and privacy preservation capability of the proposed system in the simulation-based model with no assumption. The proposed system is suitable for applications where the user does not want to reveal her biometrics to the verifier in plain form but she needs to proof her physical presence by using biometrics. The system can be used with any biometric modality and biometric feature extraction scheme whose output templates can be binarized. The overall connection time for the proposed THRIVE system is estimated to be 336 ms on average for 256-bit biohash vectors on a desktop PC running with quad-core 3.2 GHz CPUs at 10 Mbit/s up/down link connection speed. Consequently, the proposed system can be efficiently used in real life applications

On the Security Risk of Cancelable Biometrics

Over the years, a number of biometric template protection schemes, primarily based on the notion of "cancelable biometrics" (CB) have been proposed. An ideal cancelable biometric algorithm possesses four criteria, i.e., irreversibility, revocability, unlinkability, and performance preservation. Cancelable biometrics employed an irreversible but distance preserving transform to convert the original biometric templates to the protected templates. Matching in the transformed domain can be accomplished due to the property of distance preservation. However, the distance preservation property invites security issues, which are often neglected. In this paper, we analyzed the property of distance preservation in cancelable biometrics, and subsequently, a pre-image attack is launched to break the security of cancelable biometrics under the Kerckhoffs's assumption, where the cancelable biometrics algorithm and parameters are known to the attackers. Furthermore, we proposed a framework based on mutual information to measure the information leakage incurred by the distance preserving transform, and demonstrated that information leakage is theoretically inevitable. The results examined on face, iris, and fingerprint revealed that the risks origin from the matching score computed from the distance/similarity of two cancelable templates jeopardize the security of cancelable biometrics schemes greatly. At the end, we discussed the security and accuracy trade-off and made recommendations against pre-image attacks in order to design a secure biometric system.Comment: Submit to P

Improved security and privacy preservation for biometric hashing

We address improving verification performance, as well as security and privacy aspects of biohashing methods in this thesis. We propose various methods to increase the verification performance of the random projection based biohashing systems. First, we introduce a new biohashing method based on optimal linear transform which seeks to find a better projection matrix. Second, we propose another biohashing method based on a discriminative projection selection technique that selects the rows of the random projection matrix by using the Fisher criterion. Third, we introduce a new quantization method that attempts to optimize biohashes using the ideas from diversification of error-correcting output codes classifiers. Simulation results show that introduced methods improve the verification performance of biohashing. We consider various security and privacy attack scenarios for biohashing methods. We propose new attack methods based on minimum l1 and l2 norm reconstructions. The results of these attacks show that biohashing is vulnerable to such attacks and better template protection methods are necessary. Therefore, we propose an identity verification system which has new enrollment and authentication protocols based on threshold homomorphic encryption. The system can be used with any biometric modality and feature extraction method whose output templates can be binarized, therefore it is not limited to biohashing. Our analysis shows that the introduced system is robust against most security and privacy attacks conceived in the literature. In addition, a straightforward implementation of its authentication protocol is su ciently fast enough to be used in real applications

A Novel Technique for Cancelable and Irrevocable Biometric Template Generation for Fingerprints

Cancelable biometric key generation is vital in biometric systems to protect sensitive information of users. A novel technique called Reciprocated Magnitude and Complex Conjugate- Phase (RMCCP) transform is proposed. This proposed method comprises of different components for the development of new method. It is tested with the multiple aspects such as cancelability, irrevocability and security. FVC database and real time datasets are used to observe the performance on Match score using ROC, time complexity, and space complexity. The experimental results show that the proposed method is better in all the aspects of performance.