Multi-layer image encryption framework using a chaotic system with a dynamic starting point

This paper presents a novel image encryption framework that significantly enhances chaotic encryption through two synergistic innovations. First, we introduce a new class of chaotic systems based on ill-conditioned matrix operations, exhibiting extreme sensitivity to initial conditions and transforming input images into highly disordered states. Second, we propose a dynamic initialization mechanism in which encryption parameters are uniquely generated for each session by combining cryptographic keys with features extracted from the plaintext image. This approach eliminates static vulnerabilities common in conventional systems. The framework also integrates an adaptive pixel shuffling process, applying variable circular shifts governed by the evolving state of the chaotic system to effectively disrupt statistical patterns. A comprehensive security analysis demonstrates that the proposed system achieves ideal encryption metrics, including high information entropy and resistance to statistical and differential attacks.