Beta Chaotic Map Based Image Encryption Using Genetic Algorithm

2018 ◽  
Vol 28 (11) ◽  
pp. 1850132 ◽  
Author(s):  
Manjit Kaur ◽  
Vijay Kumar
Keyword(s):  
Genetic Algorithm ◽  
Image Encryption ◽  
Optimal Parameter ◽  
Fitness Function ◽  
Chaotic Map ◽  
Input Image ◽  
Experimental Results ◽  
Contourlet Transform ◽  
Nonsubsampled Contourlet Transform ◽  
Computational Speed

In this paper, an efficient image encryption technique using beta chaotic map, nonsubsampled contourlet transform, and genetic algorithm is proposed. Initially, the nonsubsampled contourlet transform is utilized to decompose the input image into subbands. The beta chaotic map is used to develop pseudo-random key that encrypts the coefficients of subbands. However, it requires certain parameters to encrypt these coefficients. A multiobjective fitness function for genetic algorithm is designed to find the optimal parameter of beta chaotic map. The inverse of nonsubsampled contourlet transform is performed to obtain a ciphered image. The performance of the proposed technique is compared with recently developed well-known meta-heuristic based image encryption techniques. Experimental results reveal that the proposed technique provides better computational speed and high encryption intensity. The comparative analyses show effectiveness of the proposed image encryption technique.

scholarly journals Image Encryption with Double Spiral Scans and Chaotic Maps

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Zhenjun Tang ◽  
Ye Yang ◽  
Shijie Xu ◽  
Chunqiang Yu ◽  
Xianquan Zhang
Keyword(s):  
Image Encryption ◽  
Chaotic Map ◽  
Input Image ◽  
Experimental Result ◽  
Image Content ◽  
Block Partition ◽  
Xor Operation ◽  
Secret Keys ◽  
Double Spiral ◽  
Image Encryption Algorithm

Image encryption is a useful technique of image content protection. In this paper, we propose a novel image encryption algorithm by jointly exploiting random overlapping block partition, double spiral scans, Henon chaotic map, and Lü chaotic map. Specifically, the input image is first divided into overlapping blocks and pixels of every block are scrambled via double spiral scans. During spiral scans, the start-point is randomly selected under the control of Henon chaotic map. Next, image content based secret keys are generated and used to control the Lü chaotic map for calculating a secret matrix with the same size of input image. Finally, the encrypted image is obtained by calculating XOR operation between the corresponding elements of the scrambled image and the secret matrix. Experimental result shows that the proposed algorithm has good encrypted results and outperforms some popular encryption algorithms.

scholarly journals A Novel Image Encryption Algorithm Based on DNA Subsequence Operation

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Qiang Zhang ◽  
Xianglian Xue ◽  
Xiaopeng Wei
Keyword(s):  
Image Encryption ◽  
Chaotic Map ◽  
Security Analysis ◽  
Experimental Results ◽  
Encryption Algorithm ◽  
Secret Key ◽  
Logistic Chaotic Map ◽  
Image Encryption Algorithm

We present a novel image encryption algorithm based on DNA subsequence operation. Different from the traditional DNA encryption methods, our algorithm does not use complex biological operation but just uses the idea of DNA subsequence operations (such as elongation operation, truncation operation, deletion operation, etc.) combining with the logistic chaotic map to scramble the location and the value of pixel points from the image. The experimental results and security analysis show that the proposed algorithm is easy to be implemented, can get good encryption effect, has a wide secret key's space, strong sensitivity to secret key, and has the abilities of resisting exhaustive attack and statistic attack.

scholarly journals Parameter estimation using the genetic algorithm and its impact on quantitative precipitation forecast

2006 ◽  
Vol 24 (12) ◽  
pp. 3185-3189 ◽  
Author(s):  
Y. H. Lee ◽  
S. K. Park ◽  
D.-E. Chang
Keyword(s):  
Genetic Algorithm ◽  
Optimal Parameter ◽  
Fitness Function ◽  
Convective Available Potential Energy ◽  
Reduction Rate ◽  
Cumulus Parameterization ◽  
Precipitation Forecast ◽  
Physical Parameters ◽  
Meteorological Model ◽  
Filter Parameter

Abstract. In this study, optimal parameter estimations are performed for both physical and computational parameters in a mesoscale meteorological model, and their impacts on the quantitative precipitation forecasting (QPF) are assessed for a heavy rainfall case occurred at the Korean Peninsula in June 2005. Experiments are carried out using the PSU/NCAR MM5 model and the genetic algorithm (GA) for two parameters: the reduction rate of the convective available potential energy in the Kain-Fritsch (KF) scheme for cumulus parameterization, and the Asselin filter parameter for numerical stability. The fitness function is defined based on a QPF skill score. It turns out that each optimized parameter significantly improves the QPF skill. Such improvement is maximized when the two optimized parameters are used simultaneously. Our results indicate that optimizations of computational parameters as well as physical parameters and their adequate applications are essential in improving model performance.

A modified method for image encryption based on chaotic map and genetic algorithm

2020 ◽  
Vol 79 (37-38) ◽  
pp. 26927-26950
Author(s):  
Mahdieh Ghazvini ◽  
Mojdeh Mirzadi ◽  
Negin Parvar
Keyword(s):  
Genetic Algorithm ◽  
Image Encryption ◽  
Chaotic Map ◽  
Modified Method

QoS Routing Optimization Based on Improved Genetic Algorithm

2014 ◽  
Vol 998-999 ◽  
pp. 1169-1173
Author(s):  
Chang Lin He ◽  
Yu Fen Li ◽  
Lei Zhang
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Computational Complexity ◽  
Fitness Function ◽  
Qos Routing ◽  
Experimental Results ◽  
Improved Genetic Algorithm ◽  
Coding Schemes ◽  
Routing Optimization

A improved genetic algorithm is proposed to QoS routing optimization. By improving coding schemes, fitness function designs, selection schemes, crossover schemes and variations, the proposed method can effectively reduce computational complexity and improve coding accuracy. Simulations are carried out to compare our algorithm with the traditional genetic algorithms. Experimental results show that our algorithm converges quickly and is reliable. Hence, our method vastly outperforms the traditional algorithms.

A Bi-objective Genetic Algorithm Optimization of Chaos-DNA Based Hybrid Approach

2019 ◽  
Vol 28 (2) ◽  
pp. 333-346 ◽  
Author(s):  
Shelza Suri ◽  
Ritu Vijay
Keyword(s):  
Genetic Algorithm ◽  
Image Encryption ◽  
Fitness Function ◽  
Hybrid Approach ◽  
Good Choice ◽  
Algorithm Optimization ◽  
Change Rate ◽  
Fitness Functions ◽  
Significant Performance ◽  
The Given

Abstract The paper implements and optimizes the performance of a currently proposed chaos-deoxyribonucleic acid (DNA)-based hybrid approach to encrypt images using a bi-objective genetic algorithm (GA) optimization. Image encryption is a multi-objective problem. Optimizing the same using one fitness function may not be a good choice, as it can result in different outcomes concerning other fitness functions. The proposed work initially encrypts the given image using chaotic function and DNA masks. Further, GA uses two fitness functions – entropy with correlation coefficient (CC), entropy with unified average changing intensity (UACI), and entropy with number of pixel change rate (NPCR) – simultaneously to optimize the encrypted data in the second stage. The bi-objective optimization using entropy with CC shows significant performance gain over the single-objective GA optimization for image encryption.

Image Encryption Algorithm Based on Even Scrambling

2011 ◽  
Vol 179-180 ◽  
pp. 470-474
Author(s):  
Jian Zhang ◽  
Hong E Ren ◽  
Yu Chen
Keyword(s):  
Image Encryption ◽  
Chaotic Map ◽  
Experimental Results ◽  
Universal Property ◽  
Encryption Algorithm ◽  
Image Scrambling ◽  
Important Method ◽  
Image Position ◽  
Image Encryption Algorithm

Image scrambling is an important method to achieve images secrecy. Arnold cat transformation is widely applied, and its scrambling effect is better relatively in the classical scrambling algorithms. But it has some shortcomings of short key qualities and poor universal property. It brings forward an algorithm of image position even scrambling through improving the Arnold cat transformation. On the basis of position scrambling, the image pixel values are scrambled using chaotic map. Experimental results show that the algorithm has many advantages of increasing key qualities obviously, satisfactory effect of scrambling, and the pixel values of the image are both changed.

scholarly journals Image Encryption based on Chaotic Map and Reversible Integer Wavelet Transform

2014 ◽  
Vol 65 (2) ◽  
pp. 90-96 ◽  
Author(s):  
Xiaopeng Wei ◽  
Bin Wang ◽  
Qiang Zhang ◽  
Chao Che
Keyword(s):  
Wavelet Transform ◽  
Image Encryption ◽  
Chaotic Maps ◽  
Chaotic Map ◽  
Experimental Results ◽  
Integer Wavelet Transform ◽  
Image Information ◽  
Initial Values ◽  
Plain Image ◽  
Integer Wavelet

Abstract In recent years, there has been growing interesting in image encryption based on chaotic maps and wavelet transform. In this paper, a novel scheme for image encryption based on chaotic maps and reversible integer wavelet transform is proposed. Firstly, the cipher key which is related to plain-image is used to generate different parameters and initial values of chaotic maps. Then the plain-image is permuted by the order from chaotic maps, and processed by integer wavelet transform. A part of transform coefficient is diffused by the orbits of chaotic maps. Finally, the cipher image is obtained by inverse integer wavelet transform based on the diffused coefficient. Numerical experimental results and comparing with previous works show that the proposed scheme possesses higher security than previous works, which is suitable for protecting the image information.

Analysis of Color Image Encryption Using Multidimensional Bogdanov Map

2021 ◽  
pp. 1410-1430
Author(s):  
R. N. Ramakant Parida ◽  
Swapnil Singh ◽  
Chittaranjan Pradhan
Keyword(s):  
Communication Network ◽  
Image Encryption ◽  
Color Image ◽  
Chaotic Map ◽  
Digital Transmission ◽  
Experimental Results ◽  
Main Concern ◽  
Single Plane ◽  
Encryption And Decryption ◽  
Two Parameters

Image encryption is a main concern in digital transmission of data over communication network. As encryption and decryption of image has got considerable attention in the past decades, its effectiveness and compatibility need to be taken care of. The work reported in this chapter is mainly concerned with enhancement of dimension in image encryption technique. The work mainly deals with pixels shuffling of an image using Bogdanov chaotic map for both gray and color image, where encryption and decryption process are associated with the key. In color image, the image is divided into all three planes (RGB) individually. Scrambling is done with all three planes individually. All the three planes are summed up into a single plane which gives us the final result. In Bogdanov map, old pixel position is replaced with new pixel position. Further, the authors analyzed security of image encryption techniques with two parameters called NPCR and UACI. The efficacy of the encryption process can be seen in experimental results.

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