摘要
针对图像传输安全问题,本文提出基于细胞神经网络CNN超混沌的特性结合一般形式的三次函数鲁棒映射和高维Lorenz系统对图像采取双扩散-置乱的加密操作.仿真结果表明本文设计的算法具有优良的加密效果,且密钥空间大、密文敏感性强、信息熵值7.9994接近理想值,能有效抵抗统计攻击等.具有一定的运用价值.
Images have become the main media active in the information age. There is no doubt about the importance of image encryption technology. In order to solve the problem of image transmission security, the proposed algorithm is based on the hyper chaotic features of cellular neural network CNN combined with the general form of cubic function robust mapping and high-dimensional Lorenz system to adopt double diffusion-scrambling encryption operation on images. The simulation results show that the algorithm designed in this paper has excellent encryption effect. Its key space is large, ciphertext sensitivity is strong, information entropy value is 7.9994 close to ideal value, and it can effectively resist statistical attacks. The algorithm in this paper has high security and certain application value.
作者
魏慧
李国东
WEI Hui;LI Guo-dong(College of Statistics and Data Science,Xinjiang University of Finance and Economics,Urumqi 830012,China;Center for Social and Economic Statistics,Xinjiang University of Finance and Economics,Urumqi 830012,China)
出处
《微电子学与计算机》
北大核心
2020年第5期43-48,53,共7页
Microelectronics & Computer
基金
国家自然科学基金(11461063)
新疆维吾尔自治区自然科基金(2017D01A24)
新疆财经大学基金(2019XTD002)。
