MODIFIED IMAGE ENCRYPTION ALGORITHM BASED ON CHAOTIC DYNAMICS

Abstract

This article examines the development of a modified image encryption algorithm based on chaotic dynamics. The relevance of the study lies in the fact that in modern telecommunications, medical, biometric, monitoring, and information systems, digital images often contain confidential data and require reliable protection against unauthorized access, substitution, and distortion. Furthermore, images possess specific properties that distinguish them from ordinary text and binary data: high correlation between adjacent pixels, significant redundancy, a two-dimensional spatial structure, and a large volume of information. For this reason, the direct application of traditional cryptographic algorithms does not always effectively disrupt the statistical structure of an image.This study is based on a hybrid approach combining chaotic transformations and standard cryptographic mechanisms. The core architecture utilizes chaotic permutation, diffusion, and subsequent authenticated AES-256-GCM encryption. This approach leverages the advantages of chaotic systems for pixel pre-shuffling and the advantages of AES-GCM for ensuring confidentiality, integrity, and data authentication. This paper proposes a modification of the algorithm based on the use of two chaotic mappings: a logistic mapping and a tent mapping. The logistic mapping is used to generate a global permutation sequence, while the tent mapping is used for block shuffling and diffusion flow generation. Additionally, the algorithm incorporates a key-dependent block permutation and double feedback diffusion. The first diffusion modifies pixel values using a chaotic pseudorandom flow, while the second creates a chain-like dependency between ciphertext bytes. This allows a change in a single pixel of the original image or a minor change in the secret key to significantly alter the final encrypted image. The key material is generated using the Scrypt function and is divided into several parts, each for AES-256-GCM, logistic mapping parameters, tent mapping parameters, block permutation, and feedback. This division increases the algorithm's sensitivity to the key and ensures the independence of individual encryption stages. To evaluate the effectiveness of the proposed algorithm, entropy, adjacent pixel correlation, histogram analysis, NPCR, and UACI metrics are used. The proposed modification is expected to improve the uniformity of pixel distribution in the encrypted image, reduce the correlation between adjacent pixels, enhance the avalanche effect, and improve resistance to statistical and differential cryptanalysis. The proposed algorithm can be used to protect images in video surveillance systems, telemedicine, biometric identification, intelligent monitoring, and secure telecommunications services.

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