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%).

在许多应用程序中，安全地处理个人的生物特征信息仍然是一个主要挑战。出于这个原因，提出了许多可取消的技术，旨在提供安全性，但最近在文献中报道了对抗性攻击，例如对流行方法的基于相似性的攻击。在本文中，我们提出了一种基于随机游走的可取消模板生成方法（二维随机游走和循环随机游走）。所提出方法的新颖之处在于从指纹数据生成安全、独特的可取消模板。此外，所提出的方案不受不同安全攻击的影响。它还保证了生成的可取消模板的随机性。我们提出的方案在平均真实接受率方面达到了可比的性能\(97.02 \%\)，不同指纹数据的平均误判率为\(0.13 \%\)。此外，我们提出的方案具有\(11.11\%\) 的FAR（攻击），与最先进的方法（例如 BioHashing 62.5%）相比，这是非常低的。