Cancellable Biometric Template Generation Using Vector Quantization and Hill Cipher

This research proposed a new method to improve the security of encrypted biometric systems by combining vector quantization with Hill ciphers. The method involves quantizing biometric data into vectors, simplifying the representation while preserving critical information, followed by encryption using a Hill cipher. This technique generates multiple secure templates from the same biometric input, providing resilience against attacks. In addition, the reversibility of the Hill cipher allows regeneration of the original biometric data under permitted conditions. The proposed system offers improved privacy, security and flexibility for modern biometric systems and demonstrates robust performance.