Abstract
In image steganography, the confidential information is hidden in a cover image to camouflage the existence of covert communication. The steganography algorithm should be highly imperceptible to avoid being detected by a visual steganalysis attack. However, at the same time, the image steganography algorithm should also have the capability to resist statistical steganalysis attacks. These statistical steganalysis attacks can be histogram attack, RS analysis, chi-square attack, etc. A genetic algorithm (GA)-based imperceptible image steganography scheme that can resist histogram attack is presented in this paper. GA is used to find suitable locations in the cover image to insert the secret message so that the data embedding process causes very few distortions in the cover image. At the same time, GA has to ensure that these locations cause very minimum histogram distortion. The proposed technique can insert the secret data at 1 bit per pixel capacity (bpp). The proposed technique yields imperceptible stego images with an average PSNR value of 51.34 dB at 1 bpp data embedding capacity.
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USC-SIPI Image Database, https://sipi.usc.edu/database/
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Shah, P.D., Bichkar, R. (2021). Genetic Algorithm-Based Imperceptible Image Steganography Technique with Histogram Distortion Minimization. In: Balas, V.E., Hassanien, A.E., Chakrabarti, S., Mandal, L. (eds) Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing. Lecture Notes on Data Engineering and Communications Technologies, vol 62. Springer, Singapore. https://doi.org/10.1007/978-981-33-4968-1_21
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DOI: https://doi.org/10.1007/978-981-33-4968-1_21
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