Developing an Algorithm for Securing the Biometric Data Template in the Database

This research article published by the International Journal of Advanced Computer Science and Applications, Vol. 10, No. 10, 2019In the current technology advancement, biometric template provides a dependable solution to the problem of user verification in an identity control system. The template is saved in the database during the enrollment and compared with query information in the verification stage. Serious security and privacy concerns can arise, if raw, unprotected data template is saved in the database. An attacker can hack the template information in the database to gain illicit access. A novel approach of encryption-decryption algorithm utilizing a design pattern of Model View Template (MVT) is developed to secure the biometric data template. The model manages information logically, the view shows the visualization of the data, and the template addresses the data migration into pattern object. The established algorithm is based on the cryptographic module of the Fernet key instance. The Fernet keys are combined to generate a multiFernet key to produce two encrypted files (byte and text file). These files are incorporated with Twilio message and securely preserved in the database. In the event where an attacker tries to access the biometric data template in the database, the system alerts the user and stops the attacker from unauthorized access, and cross-verify the impersonator based on the validation of the ownership. Thus, helps inform the users and the authority of, how secure the individual biometric data template is, and provided a high level of the security pertaining the individual data privac

Privacy-Preserving Biometric Authentication

Biometric-based authentication provides a highly accurate means of authentication without requiring the user to memorize or possess anything. However, there are three disadvantages to the use of biometrics in authentication; any compromise is permanent as it is impossible to revoke biometrics; there are significant privacy concerns with the loss of biometric data; and humans possess only a limited number of biometrics, which limits how many services can use or reuse the same form of authentication. As such, enhancing biometric template security is of significant research interest. One of the methodologies is called cancellable biometric template which applies an irreversible transformation on the features of the biometric sample and performs the matching in the transformed domain. Yet, this is itself susceptible to specific classes of attacks, including hill-climb, pre-image, and attacks via records multiplicity. This work has several outcomes and contributions to the knowledge of privacy-preserving biometric authentication. The first of these is a taxonomy structuring the current state-of-the-art and provisions for future research. The next of these is a multi-filter framework for developing a robust and secure cancellable biometric template, designed specifically for fingerprint biometrics. This framework is comprised of two modules, each of which is a separate cancellable fingerprint template that has its own matching and measures. The matching for this is based on multiple thresholds. Importantly, these methods show strong resistance to the above-mentioned attacks. Another of these outcomes is a method that achieves a stable performance and can be used to be embedded into a Zero-Knowledge-Proof protocol. In this novel method, a new strategy was proposed to improve the recognition error rates which is privacy-preserving in the untrusted environment. The results show promising performance when evaluated on current datasets

Cancellable biometric using matrix approaches

PhD ThesisCancellable biometrics endeavour to hide the appearance of a biometric image into a transformed template which prevents the outsider from recognising whom the biometric belongs to. Current research into cancellable biometric methodologies concentrates on the details of biometric traits. This approach has a drawback which cannot possibly be implemented with other biometric technology. To address this problem, this thesis contributes to development of a novel concept for the feature transformation of biometric technology, especially for fingerprints, by utilizing several matrix operations to provide an alternative algorithm in order to produce multi-implementation of the cancellable system. The matrix operations generate the feature element of the input fingerprint image in an irrevocable form of output fingerprint template by ignoring the type of biometric traits unique to fingerprints; thus, the cancellable algorithm can be implemented in different biometrics technologies. The implementation offers a new concept in generating a cancellable template by considering a sequential procedure for the fingerprint processing, in order to allow the authentication process to succeed in authenticating an enquired input. For example, a region of interest (RoI) step is required to provide a square form input to support the system working in a matrix domain. Meanwhile, the input fingerprints are mostly in rectangular form. This thesis contributes a new approach to selecting a certain area of a fingerprint by utilizing the density of ridge frequency and orientation. The implementation of these two enhancement steps reduces the excision process of this significant region of the fingerprint by avoiding the involvement of a non-feature area. Meanwhile, to avoid obtaining an un classified fingerprint, this thesis offers a new approach to the fingerprint image classification process entailing three requirements in classifying the fingerprint: the core point and its number, ridge frequency, and ridge direction; whilst the tented arch (TA) is only an additional requirement. The proposed idea increases both the percentage accuracy in classifying fingerprints and time consuming of the system. For Example, the accuracy of the fingerprint classification improves from less than 41 per cent of the fingerprint to 86.48 per cent in average for all of databases.Directorate General of Higher Education of the Ministry of Education and Culture of the Republic of Indonesi

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

A cancelable iris- and steganography-based user authentication system for the Internet of Things

Remote user authentication for Internet of Things (IoT) devices is critical to IoT security, as it helps prevent unauthorized access to IoT networks. Biometrics is an appealing authentication technique due to its advantages over traditional password-based authentication. However, the protection of biometric data itself is also important, as original biometric data cannot be replaced or reissued if compromised. In this paper, we propose a cancelable iris- and steganography-based user authentication system to provide user authentication and secure the original iris data. Most of the existing cancelable iris biometric systems need a user-specific key to guide feature transformation, e.g., permutation or random projection, which is also known as key-dependent transformation. One issue associated with key-dependent transformations is that if the user-specific key is compromised, some useful information can be leaked and exploited by adversaries to restore the original iris feature data. To mitigate this risk, the proposed scheme enhances system security by integrating an effective information-hiding technique-steganography. By concealing the user-specific key, the threat of key exposure-related attacks, e.g., attacks via record multiplicity, can be defused, thus heightening the overall system security and complementing the protection offered by cancelable biometric techniques