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A review on image steganographic techniques based on optimization algorithms for secret communication

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Abstract

This review paper explores the use of optimization techniques in steganography, the art of hiding secret information within other data. Steganography is a field that has gained significant attention in recent years due to the increasing need for secure communication and data protection. Optimization techniques have been shown to be effective in improving the performance of steganography systems, particularly in terms of maximizing the amount of secret data that can be hidden while minimizing the impact on the cover data. This paper provides a comprehensive overview of the state-of-the-art optimization techniques in steganography, including genetic algorithms, particle swarm optimization, ant colony optimization and fruit fly optimization algorithm. This paper also discusses the advantages and limitations of these techniques and their potential for further development in the future. Also the state-of-the-art methods were compared in terms of PSNR (Peak Signal to Noise Ratio), payload capacity, SSIM (Structured Similarity Index) etc. The review concludes by highlighting the importance of optimization techniques in steganography and their potential impact on the development of more efficient and secure steganography systems.

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  1. Department of ECE, Mepco Schelnk Engineering College, Sivakasi, India

    Gnanalakshmi V & Indumathi G

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  1. Gnanalakshmi V
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  2. Indumathi G
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Correspondence to Gnanalakshmi V.

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V, G., G, I. A review on image steganographic techniques based on optimization algorithms for secret communication. Multimed Tools Appl 82, 44245–44258 (2023). https://doi.org/10.1007/s11042-023-15568-7

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