<![CDATA[Secure authentication in wireless communication environments required mechanisms that were capable of verifying identity without exposing confidential information. Zero-Knowledge Authentication addressed this challenge by enabling interactive identity verification without revealing secret credentials however, its performance strongly depended on the reliability of the cryptographic key generation process. This study investigated the use of Received Signal Strength as a source for cryptographic key generation and addressed the instability caused by noise and signal fluctuation in wireless channels. A preprocessing approach based on the Kalman Filter was proposed to improve the quality of Received Signal Strength measurements prior to key generation. The Kalman Filter was applied to reduce noise and enhance signal reciprocity between communicating nodes, ensuring that both parties generated identical cryptographic keys. The filtered signal values were then utilized to support the Zero Knowledge Feige-Fiat-Shamir authentication mechanism by replacing the conventional communication channel with keys derived from the preprocessed signal measurements.The performance of the proposed approach was evaluated through key consistency, entropy level, and bit mismatch rate between legitimate nodes. The experimental results showed that Kalman Filter–based preprocessing improved the stability of Received Signal Strength measurements and significantly increased the consistency of generated keys compared to unfiltered approaches. Consequently, the authentication success rate was enhanced while maintaining the confidentiality properties of Zero-Knowledge Authentication. These findings demonstrated that Kalman Filter assisted preprocessing effectively strengthened the security and reliability of cryptographic key generation for wireless Zero-Knowledge authentication systems.]]>
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