Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : kinetik game technology information system computer network computing electronics and control

Kalman Filter-Based RSS Preprocessing for Cryptographic Key Generation in Zero-Knowledge Feige Fiat Shamir Authentication M. Cahyo Kriswantoro; Eko Handoyo; Ahmad Lathif Aditya
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 3, August 2026
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i3.2644

Abstract

Secure authentication in wireless communication environments requires mechanisms capable of verifying identity without exposing confidential information. Zero-Knowledge Authentication (ZKA) addresses this challenge by enabling interactive identity verification without revealing secret credentials. However, in practical wireless implementations, the reliability of ZKA strongly depends on the quality and consistency of the cryptographic keys used during the authentication process. One promising approach is to generate keys from physical-layer characteristics, such as Received Signal Strength (RSS). Nevertheless, raw RSS measurements are highly unstable due to noise, interference, mobility, and signal fluctuations, which often result in low reciprocity and key mismatch between legitimate nodes. This study proposes a Kalman Filter-based preprocessing method to improve RSS quality prior to cryptographic key generation for Zero-Knowledge Feige–Fiat–Shamir authentication. The Kalman Filter is employed to suppress measurement noise and enhance reciprocity between communicating nodes, allowing both parties to derive more consistent symmetric keys. The generated keys are then integrated into the authentication process to replace conventional static, channel-dependent key components. The proposed approach was evaluated using key consistency, entropy level, and bit mismatch rate as performance metrics. Experimental results show that Kalman Filter-based preprocessing significantly improves RSS stability and increases the correlation between legitimate nodes compared with unfiltered RSS measurements. In addition, the generated keys exhibit lower bit mismatch rates and better entropy characteristics, leading to higher authentication success rates while preserving the confidentiality properties of Zero-Knowledge Authentication. These findings demonstrate that Kalman Filter-assisted RSS preprocessing provides an effective and lightweight solution for strengthening cryptographic key generation and improving the reliability of authentication systems in wireless communication environments.