LCA approach for Image Encryption Based on Chaos to Secure Multimedia Data in IoT

Seema Nath, S. Som, M. Negi
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引用次数: 2

Abstract

Recently, improvement of the internet usages, huge amount of multimedia data is transmitted through the network. The encryption method is introduced to secure the multimedia data for improve individual privacy, copyrights and other security reasons. In this paper proposed the LCA algorithm for chaotic logistic map based image encryption. Trendy this map of logistic parameter tuning is attained with the help of the LCA algorithm. The LCA algorithm is working based on the competition of sports teams in a league match. Various people as game groups contend in a league match for a few weeks; founded on the LCA process, logistic maps are tuned. The proposed algorithm for encryption is process constructed scheduled the two tasks such as confusion in addition diffusion. In confusion, produce the cipher image from the plain image by conversion. Second, the diffusion procedure is developed to diffuse the sequences equally. Here, the logistic maps parameters are taken as the encryption key. To prove the secure and reliable of the technique of proposed which is executed in the MATLAB and simulation results and performance analysis are described popular in paper. The presentation of proposed technique be there analysis through the way, statistical test and security test which is competitive with other freshly developed image encryption algorithm. To prove the efficiency of the proposed method which paralleled with the existing methods such as Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) respectively.
基于混沌的物联网多媒体数据安全图像加密LCA方法
近年来,随着互联网使用水平的提高,大量的多媒体数据通过网络传输。从保护个人隐私、保护版权等方面考虑,采用加密的方法对多媒体数据进行安全保护。提出了一种基于混沌逻辑映射的图像加密LCA算法。在此基础上,利用LCA算法得到了logistic参数整定图。LCA算法是基于联赛中运动队的竞争而工作的。不同的人作为游戏群体在一个联赛中竞争几个星期;在LCA过程的基础上,对逻辑图进行了调整。所提出的加密算法是将混淆和扩散这两个任务调度的过程。在混乱的情况下,通过转换将明文图像生成密码图像。其次,建立了扩散过程,使序列均匀扩散。这里以逻辑映射参数作为加密密钥。为了证明该技术的安全性和可靠性,本文在MATLAB中进行了仿真,并给出了仿真结果和性能分析。本文提出的算法经过了方法分析、统计测试和安全性测试,与其他新开发的图像加密算法相比具有一定的竞争力。通过与现有的萤火虫算法(FA)和粒子群算法(PSO)的对比,验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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