Developing a model for securing bio metric recognition systems used in nuclear facilities

Nowadays, bio metric identification systems provide a reliable solution for identity verification that allows restrictive access to nuclear facilities by unauthorized personnel. Bio metric identification systems offer enhanced accuracy, improved accountability, and a reduction in opportunities for misuse, compared to other traditional identification systems that relay on passwords, ID cards, or personal identification numbers (PINs). However, biometrics also have some specific security/privacy issues. For example, biometrics are vulnerable to be captured easily without the user's consent. Also, if a user bio metric is exposed once, it is compromised forever, because it is always associated with the user and cannot be replaced or cancelled. Moreover, bio metric-based authentication methods depend on the same biometrics. So, if a bio metric template is compromised in an application, then the same method can be used to access other applications at which the same bio metric is used. Furthermore, while relative robustness over time is an advantage for biometrics, it can also be a massive challenge from the privacy point of view, when the bio metric needs to be changed. So, biometrics definitely are sensitive data, and therefore they should be properly secured, because they may be misused by any attackers. Therefore, integrating a high security solution into the bio metric recognition system to protect personal information during storage, and transmission is a necessity. In spite of proposing several methods for preserving the privacy and security of the individual bio metric data, this comes at the expense of decreasing the performance accuracy in comparison to traditional unprotected bio metric recognition systems. This motivates us to design a new lightweight, robust and secure technique for enhancing the security of bio metric recognition systems without affecting the performance accuracy. This thesis presents a novel model for securing iris recognition systems by using a combination of cancellable Iris Code generation based on salting approach and iris cryptosystem based on elliptic curve cryptography. In this model, a cancellable Iris Code is generated by combining the original binary Iris Code with a totally artificial cover pattern (synthetic pattern) in a piel-wise manner using XOR operation.Once the non-invertible transformed version is obtained from the enrolled Iris Code, the original bio metric pattern is discarded. The matching stage is made primarily on the resultant distorted cancellable iris pattern. Then, the cancellable Iris Code is divided into binary blocks. Each binary block is mapped to a point on the elliptic curve, and then encrypted based on elliptic curve encryption, generating a protected Iris Code. Hence, the protected Iris Code can be stored and transmitted more securely. This model guarantees a high degree of privacy/security protection without affecting the performance accuracy compared to the unprotected traditional iris bio metric system. The proposed technique has been analyzed in the absence and presence of different types of noises, and then compared with the traditional unprotected iris recognition technique. Robustness to scaling effects as well as security of the proposed technique has been evaluated. Furthermore, a comparative study of the proposed technique with the existing iris protection techniques is presented and discussed.