<p>In the context of modern network security, traditional authentication methods such as passwords and PINs are increasingly vulnerable to attacks like phishing, hacking, and credential theft. Biometric authentication has emerged as a promising solution, offering higher security levels by leveraging unique biological traits such as fingerprints, facial features, or iris patterns. However, the immutability of biometric data presents a significant risk in case of data breaches, as once compromised, it cannot be changed or revoked. Cancellable biometric systems are an effective approach to enhance security and privacy in network access control. Unlike traditional cryptosystems, they provide template revocability and diversity. Other approaches for biometric data protection include biometric cryptosystems, secure template storage, homomorphic encryption, and multi-factor authentication, which can complement or serve as alternatives depending on the application scenario. The cancellable biometric framework aims to provide a secure and revocable alternative to traditional biometric systems by transforming biometric data into a cancellable representation that can be altered or revoked if compromised. In case of a breach, a new template can be generated without affecting the user’s privacy or requiring biometric data re-registration. This paper present an efficient algorithm for cancellable biometric depending on FWHT with a simple scan pattern encryption algorithm. Through extensive evaluation, we demonstrate that the proposed system maintains high authentication accuracy while offering a flexible, privacy-preserving solution for secure network access. Two different biometrics have been used (Voice, ECG and face) to test our system, and a remarkably high Area under the ROC curve of nearly 99.9% is obtained for the three datasets. These results underscore the framework’s potential in securing networks through cancellable biometrics.</p>