As digital communication and storage continue to expand, the protection of image privacy information becomes increasingly critical. To safeguard sensitive visual information from unauthorized access, this paper propos...
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As digital communication and storage continue to expand, the protection of image privacy information becomes increasingly critical. To safeguard sensitive visual information from unauthorized access, this paper proposes a novel image encryption scheme that integrates multiobjective Artificial Bee Colony (abc) optimizationalgorithm and DNA coding. Multiple evaluation metrics including correlation relationship, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), and information entropy are collaboratively optimized by the abcalgorithm. The proposed method begins with the application of the SHA-256 algorithm to generate keys and random sequences using chaotic systems. These sequences are then employed for shuffling, DNA coding, decoding, and diffusion, generating initial encrypted images. Subsequently, the encrypted images serve as individuals within the abcalgorithm to determine optimal parameters of the chaotic systems and the best ciphertext image. Simulation experiments demonstrate that the ciphertext images achieved excellent results in information entropy, pixel correlation coefficient, NPCR, and UACI. The integration of the multiobjective abc optimization algorithm with DNA coding in our proposed image encryption scheme results in heightened security, as evidenced by superior performance in various metrics.
Securing digital images againstmodern attacks is a hot research topic in the field of cryptography. Several encryption schemes have been proposed, but either they do not achieve high security or they are computational...
详细信息
Securing digital images againstmodern attacks is a hot research topic in the field of cryptography. Several encryption schemes have been proposed, but either they do not achieve high security or they are computationally costly for any image, and thus may not be suitable for real-time applications. We design an image encryption scheme by formulating an optimization problem with an objective function that captures both entropy and correlation. We select a core of the plain-image to compute a parameter that optimizes the objection function over the core using artificial bee colony (abc) algorithm. Furthermore, we propose a new efficient random number generator over isomorphic elliptic curves. This generator together with the parameter is then used to generate cipher-images. The strength of the proposed random number generator and encryption scheme is analyzed by applying several standard tests. Detailed experimental results reveal that our scheme achieved entropy, correlation, number of pixel change rate and unified average changing intensity close to the theoretically optimal values, and is up to 5 x 10(4) times faster than the existing schemes.
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