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Selective Color Image Encryption Based on MSB and Sensitive Bits


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Received: 6 July 2025; Revised: 17 August 2025; Accepted: 22 August 2025; Published: 8 September 2025
This paper introduces a selective image encryption framework for color imagery, emphasizing computational efficiency without compromising practical security. The core idea is to encrypt only the most informative and perceptually critical components of each pixel, while bypassing nonessential data to reduce processing cost; a full-encryption variant is implemented to enable apples-to-apples comparison. Evaluated on a representative set of natural color images, the selective scheme achieves encrypted outputs with an average Peak Signal-to-Noise Ratio (PSNR) of 8.7 dB, Mean Structural Similarity (MSSIM) of 0.07, and Information Entropy (IE) of 7.8 bits. These values are closely aligned with those obtained under full encryption, indicating low residual similarity to the plaintext and near-uniform randomness in cipher histograms. In qualitative terms, the visual content is thoroughly obfuscated, while the selective strategy decreases the amount of data entering the cryptographic core, yielding measurable speedups. The design integrates permutation and diffusion stages suitable for block-based processing and common cipher modes, and supports region-of-interest operation when desired. Together, the empirical evidence and design choices suggest a practical trade-off: comparable security indicators at a fraction of the computational effort. The approach is particularly attractive for resource-constrained settings, batch protection of large image corpora, and latency-sensitive pipelines. Future work will extend the methodology to grayscale imagery, broaden the testbed, and incorporate a dedicated pseudo-random number generator to decouple randomness from platform dependencies.
Keywords:
Selective Image Encryption Region of Interest (ROI) MSB Fisher–Yates Shuffling CBC Information EntropyReferences
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