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

Cancelable iris Biometrics based on data hiding schemes

The Cancelable Biometrics is a template protection scheme that can replace a stolen or lost biometric template. Instead of the original biometric template, Cancelable biometrics stores a modified version of the biometric template. In this paper, we have proposed a Cancelable biometrics scheme for Iris based on the Steganographic technique. This paper presents a non-invertible transformation function by combining Huffman Encoding and Discrete Cosine Transformation (DCT). The combination of Huffman Encoding and DCT is basically used in steganography to conceal a secret image in a cover image. This combination is considered as one of the powerful non-invertible transformation where it is not possible to extract the exact secret image from the Stego-image. Therefore, retrieving the exact original image from the Stego-image is nearly impossible. The proposed non-invertible transformation function embeds the Huffman encoded bit-stream of a secret image in the DCT coefficients of the iris texture to generate the transformed template. This novel method provides very high security as it is not possible to regenerate the original iris template from the transformed (stego) iris template. In this paper, we have also improved the segmentation and normalization process

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

Biometric identification and recognition for IRIS using Failure Rejection Rate (FRR) / Musab Ahmed Mohammed Ali Al-Rawi

Iris recognition is reckoned as one of the most reliable biometrics for identification purpose in terms of reliability and accuracy. Hence, the objectives of this research are new algorithms development significantly for iris segmentation specifically the proposed Fusion of Profile and Mask Technique (FPM) specifically in getting the actual center of the pupil with high level of accuracy prior to iris localization task, followed by a particular enhancement in iris normalization that is the application of quarter size of an iris image (instead of processing a whole or half size of an iris image) and for better precision and faster recognition with the robust Support Vector Machine (SVM) as classifier. Further aim of this research is the integration of cancelable biometrics feature in the proposed iris recognition technique via non-invertible transformation which determines the feature transformation-based template protection techniques security. Therefore, it is significant to formulate the noninvertibility measure to circumvent the possibility of adversary having the capability in guessing the original biometric providing that the transformed template is obtained. At any process of recognition stage, the biometric data is protected and also whenever there is a compromise to any information in the database it will be on the cancelable biometric template merely without affecting the original biometric information

A New Biometric Template Protection using Random Orthonormal Projection and Fuzzy Commitment

Biometric template protection is one of most essential parts in putting a biometric-based authentication system into practice. There have been many researches proposing different solutions to secure biometric templates of users. They can be categorized into two approaches: feature transformation and biometric cryptosystem. However, no one single template protection approach can satisfy all the requirements of a secure biometric-based authentication system. In this work, we will propose a novel hybrid biometric template protection which takes benefits of both approaches while preventing their limitations. The experiments demonstrate that the performance of the system can be maintained with the support of a new random orthonormal project technique, which reduces the computational complexity while preserving the accuracy. Meanwhile, the security of biometric templates is guaranteed by employing fuzzy commitment protocol.Comment: 11 pages, 6 figures, accepted for IMCOM 201