Abstract
Image steganography has been widely adopted to protect confidential data. Researchers have been seeking to improve the steganographic techniques in order to increase the embedding capacity while preserving the stego-image quality. In this paper, we propose a steganography method using particle swarm optimization and chaos theory aiming at finding the best pixel locations in the cover image to hide the secret data while maintaining the quality of the resultant stego-image. To enhance the embedding capacity, the host and secret images are divided into blocks and each block stores an appropriate amount of secret bits. Experimental results show that the proposed scheme outperforms existing methods in terms of the PSNR and SSIM image quality metrics.
Highlights
Information security has become a major topic due to its important role in data communication
We propose a chaotic Particle swarm optimization (PSO) (CPSO) algorithm to make the PSO algorithm progressively effective in the steganography process by locating the best pixel locations in the cover image to embed the secret image bits while maintaining the quality of the stego-image resulting from the embedding process
We consider two parameters for evaluation: the embedding capacity and the quality of the stego-image. e capacity is measured by the number of secret bits that are embedded in the cover image. e quality of the stego-image can be measured by different metrics such as peak signal to noise ratio (PSNR) and structural similarity index (SSIM)
Summary
Information security has become a major topic due to its important role in data communication. E PSO algorithm aims to work in a collective and cooperative manner in a smart way It appeared in 1995 and witnessed a number of enhancements in many areas, as it is closely linked to the evolutionary algorithms and artificial life [8]. It has many advantages including the following: (a) it does not require a large number of control parameters, so it is anything but not difficult to execute; (b) it can be accomplished through balanced computing as it is applied to gathering of particles. More insights on the logistic map are given
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