In this paper, an effective method named Exponential Fractional-Cat Swarm Optimization (Exponential Fractional-CSO) along with multi-objective cost function is proposed. The proposed method is designed by integrating the CSO with the fractional concept based on the Exponential parameters. Initially, an input video is selected from the database from which frames are generated. Key frames are chosen among the frames using the contourlet transform and Structural Similarity Index Measure (SSIM). Regions are formed on the selected key frames through the help of grid lines. Once the regions are formed, optimal regions are ascertained with the help of the proposed optimization algorithm along with multi-objective cost functions to hide the secret data. During the embedding process, the secret data is hidden in the optimal region using the lifting wavelet transform (LWT). The embedded video is then transmitted through the network to reach its intended receiver. The experimental results reveal that the proposed Exponential Fractional-CSO obtained a maximal correlation of 0.9931 by considering the frames, maximal Peak Signal-to-Noise Ratio (PSNR) of 89.70 dB and MSE of 0.00006 respectively. Hence, the proposed method shows greater effectiveness of hiding the secret data in the video sequence along with data security.

本文提出了一种有效的方法，称为指数分数猫群优化算法（Exponential Fractional-CSO）以及多目标成本函数。通过将CSO与基于指数参数的分数概念集成来设计所提出的方法。最初，从数据库中选择输入视频，并从中生成帧。使用Contourlet变换和结构相似性指标度量（SSIM）从帧中选择关键帧。通过网格线在选定的关键帧上形成区域。一旦形成区域，就可以借助所提出的优化算法以及多目标成本函数来确定最佳区域，以隐藏秘密数据。在嵌入过程中，使用提升小波变换（LWT）将秘密数据隐藏在最佳区域中。然后，嵌入式视频将通过网络传输到其预期的接收器。实验结果表明，通过考虑帧，建议的最大峰值信噪比（PSNR）为89.70 dB和MSE为0.00006，所提出的指数分数CSO的最大相关性为0.9931。因此，所提出的方法显示出在视频序列中隐藏秘密数据以及数据安全性的更大有效性。70 dB和MSE分别为0.00006。因此，所提出的方法显示出在视频序列中隐藏秘密数据以及数据安全性的更大有效性。70 dB和MSE分别为0.00006。因此，所提出的方法显示出在视频序列中隐藏秘密数据以及数据安全性的更大有效性。