This study explores the integration of eye-tracking technology, specifically the gaze point (GP3) eye tracker, to develop a novel encryption and decryption model that leverages an individual's unique eye patterns as a cryptographic key. This research addresses the critical problem of balancing user-friendly encryption mechanisms with robust security. This study aims to design a gaze-based encryption system that uses the eye's binary matrix as a dynamic encryption key. The methodology involves capturing an eye image, converting it into a binary matrix, and using the extracted matrix to generate a unique iris key (IK) applied to encrypt and decrypt text messages on the basis of gaze interaction. This study evaluates the proposed approach against metrics such as encryption and decryption time, key entropy, and resilience to cryptanalysis. The results demonstrate that the system achieves high levels of security, with the iris key offering sufficient randomness and robustness against brute-force attacks. The gaze-based mechanism reveals hidden text when the user interacts with specific characters, enhancing privacy. The proposed model integrates biometric authentication with real-time e
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