With the explosive growth of digital data, ensuring file integrity and authenticity has become increasingly critical. Traditional hash functions such as MD5 and SHA-2, while widely adopted, face vulnerabilities against collision and preimage attacks. This project proposes a novel keyed hash function based on compounded chaotic maps, leveraging the inherent unpredictability and sensitivity to initial conditions of chaotic systems. By iteratively applying multiple chaotic maps with user-selected secret parameters, the proposed scheme generates highly diffuse, collision-resistant hash values that are keyed—thus preventing adversaries without the key from forging valid hashes. Integrated into a Django-based client–server framework, the system supports secure file upload, download, and integrity verification for both end users and administrators. Performance evaluations demonstrate that our chaotic-map-based hash achieves comparable throughput to conventional algorithms while offering enhanced resistance to differential and statistical attacks. This work outlines the mathematical foundations of compounded chaotic mapping, details the system architecture, and presents empirical security analyses showing strong avalanche effects and collision resistance.

Keywords: Compounded chaotic maps, Keyed hash function, File integrity verification, Chaotic hashing.