Graph signal processing and tunicate swarm optimization based image steganography using hybrid chaotic map based image scrambling

Shikha Chaudhary, Saroj Hiranwal, C. Gupta
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Abstract

Abstract This paper put forwards a secure image steganography technique for transmitting sensitive data using a Tunicate swarm optimization algorithm. A hybrid chaotic map-based image scrambling method is proposed with the combination of Tent and Tinkerbell chaotic maps. The scrambling of the secret image provides an added level of security in data hiding. The graph signal processing of cover image using the Meyer wavelet filter is performed to conceal the secret data within the transformed cover image using the alpha blending operation. To discover the optimal value of alpha for alpha blending, the tunicate swarm optimization algorithm is employed. To take the hidden information out at receiver end, the reverse approach is applied. The experimental results revealed that the embedding technique using the tunicate algorithm with a hybrid chaotic map provides better imperceptibility and robustness in comparison to the existing graph signal-based image steganography technique. The investigation is done on PSNR, MSE and SSIM performance parameters for evaluating the proposed technique.
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基于混合混沌映射置乱的图形信号处理和束状虫群优化图像隐写
摘要:提出了一种利用束状虫群优化算法实现敏感数据传输的安全图像隐写技术。提出了一种将Tent混沌映射与Tinkerbell混沌映射相结合的混合混沌映射图像置乱方法。对秘密图像的置乱为数据隐藏提供了额外的安全级别。利用Meyer小波滤波器对封面图像进行图形信号处理,利用alpha混合操作隐藏变换后的封面图像中的秘密数据。为了找到用于混合的最优alpha值,采用了束状虫群优化算法。为了在接收端取出隐藏信息,采用了相反的方法。实验结果表明,与现有的基于图信号的图像隐写技术相比,基于混合混沌映射的束状图算法嵌入技术具有更好的隐蔽性和鲁棒性。通过对PSNR、MSE和SSIM性能参数的研究,对该技术进行了评价。
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CiteScore
3.10
自引率
21.40%
发文量
126
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