Chaotic coyote optimization algorithm for image encryption and steganography

It is significant to ensure the communication networks and information security, and balancing simplicity and complexity is still a real issue that is the key to improve the effectiveness of a scheme in many applications scenarios.Current researches focusing on the security of digital images and put...

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Veröffentlicht in:Multimedia tools and applications 2024-02, Vol.83 (7), p.20861-20887
Hauptverfasser: Tong, Huawei, Li, Tianyou, Xu, Youyun, Su, Xinzhong, Qiao, Guopeng
Format: Artikel
Sprache:eng
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Zusammenfassung:It is significant to ensure the communication networks and information security, and balancing simplicity and complexity is still a real issue that is the key to improve the effectiveness of a scheme in many applications scenarios.Current researches focusing on the security of digital images and putting barriers to protect sensitive data still have room for improvement. Herein,the aim of this paper is twofold. Firstly, we propose a color image encryption method by utilizing Chaotic Coyote Optimization Algorithm to solve the key selection problem for minimizing the correlation between adjacent pixels of the cipher image, where three color channels are processed to enhance its security against various attacks. Secondly, we design a color image Steganography scheme that has ability to defend common types of the image attacks. In the design stage of embedding, the Chaotic Coyote Optimization Algorithm and a special designed strategy are implemented together to handle the problem of location selection to lower the distortion in all components of the embedded image. According to the simulation results, the proposed image encryption method is efficient and robust considering the performance indexes: correlation coefficient, information entropy, number of pixels change rate, unified average changing intensity, and histogram. Meanwhile, the image Steganography approach also provides satisfying effect compared with other methods in the literature, based on indicators of peak signal-to-noise ratio and structural similarity.
ISSN:1573-7721
1380-7501
1573-7721
DOI:10.1007/s11042-023-16240-w