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Optimized video steganography using Cuckoo Search algorithm

机译:使用杜鹃搜索算法优化视频隐写术

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摘要

Steganography is a process of concealing the secret information into cover object such as text, audio, image, and video. In this paper, we propose a new treatment of Cuckoo Search (CS) algorithm to solve the problem of video steganography. CS is a metaheuristic search algorithm which was recently devolved by Xin-She Yang and Suash Deb in 2009, inspired by the cuckoo bird breeding behavior. The suggested algorithm is based on taking secret data byte by byte. The bits of each byte are arranged to obtain five different forms. The next step focuses on searching about the best carrier pixel in the cover frame. The best pixel is determined using Euclidian distance which evaluate the similarity between the pixels and different byte forms. The random move from pixel to another is achieved using Lévy flight random walk. Finally, the suitable carrier pixel is detected and embedded in its RGB components using the 3-3-2 Least Significant Bit (LSB) replacement technique. In addition, each secret image's color component is embedded separately into a selected cover video's frame. Results show that CS is superior to Genetic Algorithm (GA) and the base technique in term of Peak Signal to Noise Ratio (PSNR).
机译:隐写术是将秘密信息隐藏到诸如文本,音频,图像和视频之类的掩盖对象中的过程。在本文中,我们提出了一种新的Cuckoo Search(CS)算法,以解决视频隐写技术的问题。 CS是一种元启发式搜索算法,受杜鹃鸟的繁殖行为启发,最近由杨新社和Suash Deb于2009年提出。建议的算法基于逐字节获取秘密数据。每个字节的位被安排以获得五种不同的形式。下一步着重于搜索封面帧中最佳的载体像素。使用欧几里得距离确定最佳像素,该距离评估像素与不同字节形式之间的相似性。使用Levy飞行随机游走可以实现从像素到另一个的随机移动。最后,使用3-3-2最低有效位(LSB)替换技术来检测合适的载波像素并将其嵌入RGB分量中。此外,每个秘密图像的颜色分量分别嵌入到所选封面视频的帧中。结果表明,CS在峰值信噪比(PSNR)方面优于遗传算法(GA)和基本技术。

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