A Simple and Robust Gray Image Encryption Scheme Using Chaotic Logistic Map and Artificial Neural Network

Abstract

A robust gray image encryption scheme using chaotic logistic map and artificial neural network (ANN) is introduced. In the proposed method, an external secret key is used to derive the initial conditions for the logistic chaotic maps which are employed to generate weights and biases matrices of the multilayer perceptron (MLP). During the learning process with the backpropagation algorithm, ANN determines the weight matrix of the connections. The plain image is divided into four subimages which are used for the first diffusion stage. The subimages obtained previously are divided into the square subimage blocks. In the next stage, different initial conditions are employed to generate a key stream which will be used for permutation and diffusion of the subimage blocks. Some security analyses such as entropy analysis, statistical analysis, and key sensitivity analysis are given to demonstrate the key space of the proposed algorithm which is large enough to make brute force attacks infeasible. Computing validation using experimental data with several gray images has been carried out with detailed numerical analysis, in order to validate the high security of the proposed encryption scheme.

Digital Image Encryption Techniques: Article Review

“…In which p (mi) represents likelihood of a pixel and N represents number of the bits in every one of the pixels. For graylevel images, every one of the pixels has 8 bits, which is why, the pixel probability is 1∕ 2 8 . As a result, a graylevel image's information entropy is H (m) = 8.…”

“…Image encryption methods majorly use three approaches: (1) pixel permutation: the pixels are scrambled by the algorithm [5,6], (2) pixel substitution: the pixel value is modified by the encryption technique, and (3) visual transformation. Because of its non-linear and one-way features, artificial neural network (ANN) represents unique method for the implementation of image protection [8,9]. Calculating the end result in ANN is simple; however, getting raw data from the conclusion is a difficult issue.…”

Optimized Energy Efficient Secure Routing Protocol for Wireless Body Area Network

“…The authors identified that symmetric cryptographic protocols are prone to active and passive hacker attacks. To overcome passive attacks, chaotic map-based systems are preferred due to generation of random and non-periodic shared secret key [39]- [43]. This proposed solution turned out to be feasible as the mean CPU execution time for cryptographic process was very low and uses less computational resources than Chaotic Synchronization Cryptographic System (CSCS).…”

An efficient color image encryption scheme based on a matrix scrambling method and a new hybrid chaotic map

“…Chaos in nonlinear dynamics systems has been attracted much attention of several different scientific areas especially in engineering science such as secure communication, cryptography and steganography for the last decades. For instance, chaos is applied in communication systems in An et al (2011), Eisencraft et al (2012), Hu et al (2010), Jiang et al (2011), Kaddoum et al (2010), Kang et al (2014), Ryu and Lee (2013), Türk and Oğraş (2011), Yang et al (2015), Yang and Zhu (2013); used for image cryptosystems in , Z. L. Zhu et al (2011), Murillo-Escobar et al (2015), Oğraş and Türk (2016), Patidar et al (2011), Telem et al (2014), Wang et al (2011), Ye (2011), Ye and Guo (2014), N. Zhou et al (2011), and H. Zhu et al (2013); for power systems in Yibei et al (2011), Ginarsa et al (2013), Yau et al (2015), Ghasemi et al,(2014), ; X. Zhou et al (2012); Tur and Ogras (2021); for Steganographic systems in Ogras (2019), Kar et al (2018), Bilal et al (2014), Battikh et al (2014), and Saeed (2013).…”