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An efficient image encryption using deep neural network and chaotic map

机译:使用深神经网络和混沌映射的有效图像加密

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摘要

Inspite of progressive growth of cryptography, encrypting sensitive information of an image is still a computationally complex task. After reviewing existing literature, it is now known that security problems are yet not solved and there is an open scope of further research. In most recent times, it has been noticed that neural network has proven cost effective optimization mechanism in offering security towards images. However, such implementation are computationally expensive process and do not solve various diversified attacks on image. Hence, the prime purpose of proposed system is to introduce an analytical research methodology for presenting a sophisticated framework where deep neural network has been used for optimizing the performance of simple encryption approaches. The robustness of optimization principle is further added with chaotic map concept for enhanced security performance. The study outcome shows that proposed implementation offers much better security performance without any negative effect on image quality. (c) 2020 Elsevier B.V. All rights reserved.
机译:密码术的渐进性增长,加密图像的敏感信息仍然是一个计算复杂的任务。在审查现有文献之后,现在已知安全问题尚未解决,并且有一个开放的进一步研究范围。在最近的时间内,已经注意到神经网络已经证明了在为图像提供安全性的成本有效的优化机制。然而,这种实现是计算昂贵的过程,并且不解决对图像的各种多样化攻击。因此,所提出的系统的主要目的是引入分析研究方法,以提出一种复杂的框架,其中深神经网络已被用于优化简单加密方法的性能。优化原理的稳健性进一步添加了混沌映射概念,以提高安全性能。研究结果表明,拟议的实施提供了更好的安全性能,对图像质量没有任何负面影响。 (c)2020 Elsevier B.v.保留所有权利。

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