Attack-Resistant and Efficient Cancelable Codeword Generation Using Random walk-Based Methods

Securely handling the biometric information of an individual is still a major challenge in many applications. For this reason, many cancelable techniques are present which were proposed with an aim to provide security, but adversarial attacks like a similarity-based attack on popular methods have recently been reported in the literature. In this paper, we propose a random walk-based method for cancelable template generation (2-d random walk and circular random walk). The novelty of the proposed method is to generate a secure, distinct cancelable template from fingerprint data. Further, the proposed scheme is immune to different security attacks. It also ensures the randomness of the generated cancelable templates. Our proposed scheme achieves comparable performance in terms of average genuine acceptance rate of \(97.02 \%\), average false acceptance rate of \(0.13 \%\) for different fingerprint data. Moreover, our proposed scheme has FAR (attack) of \(11.11\%\), which is very low compared to the state-of-the-art method (such as BioHashing 62.5%).