A Novel Hyperchaotic Image Encryption System Based on Particle Swarm Optimization Algorithm and Cellular Automata

Abstract

In this paper, we propose a hyperchaotic image encryption system based on particle swarm optimization algorithm (PSO) and cellular automata (CA). Firstly, to improve the ability to resist plaintext attacks, the initial conditions of the hyperchaotic system are generated by the hash function value which is closely related to the plaintext image to be encrypted. In addition, the fitness of PSO is the correlation coefficient between adjacent pixels of the image. Moreover, On the basis of hyperchaotic system, cellular automata technology is adopted, which can enhance the randomness of population distribution and increase the complexity and diversity of the population so that the security of the encryption system can be improved and avoid falling into local optimum. The simulation results and security analysis of the proposed encryption system demonstrate that the hyperchaotic image encryption system has high resistance against plaintext attack and statistical attack.

Design and FPGA Implementation of a Pseudo-random Number Generator Based on a Hopfield Neural Network Under Electromagnetic Radiation

“…In recent years, image and video encryption based on chaotic system has been widely studied and applied [51][52][53][54][55][56]. As the main application of chaotic system, PRNG has been paid more and more attention in the field of image encryption [57][58][59].…”

Chaotic Map Optimization for Image Encryption Using Triple Objective Differential Evolution Algorithm

“…In general, they are based on logistic [11], [12], [15], [17], [18], [21], [25], sine/cosine [23], [25], [29], memristive [24], henon [29], Chebyshev [32], coupled lattice [10] and cellular automata [31], [40]. As the cryptanalyses are compared among each other, the key-spaces in [10], [19], [22]- [24], [28], [32] can be regarded the shorter, those in [14], [18], [26], [36] are medium and those in [11], [16], [20], [21], [25], [29], [34], [35], [40], [41] are considered the longer. The mean entropy can be quantized better [20], moderate [14], [24]- [31], [41] and worse [10], [11], [15], [18], [19], [21],…”

“…As the cryptanalyses are compared among each other, the key-spaces in [10], [19], [22]- [24], [28], [32] can be regarded the shorter, those in [14], [18], [26], [36] are medium and those in [11], [16], [20], [21], [25], [29], [34], [35], [40], [41] are considered the longer. The mean entropy can be quantized better [20], moderate [14], [24]- [31], [41] and worse [10], [11], [15], [18], [19], [21], [32]- [34], [40]. As the mean correlation coefficients for diagonal, horizontal and vertical directions in [11], [12], [14], [24] seem lower, those in [15], [16], [31]- [36], [40], [41], [19]- [21], [23], …”

“…The mean entropy can be quantized better [20], moderate [14], [24]- [31], [41] and worse [10], [11], [15], [18], [19], [21], [32]- [34], [40]. As the mean correlation coefficients for diagonal, horizontal and vertical directions in [11], [12], [14], [24] seem lower, those in [15], [16], [31]- [36], [40], [41], [19]- [21], [23], [26]- [29] appears moderate and those in [10], [13], [18], [25], [30] look higher. Differential attack can be analyzed in terms of NPCR and UACI which are the randomness test.…”

An amplitude-controllable 3-D hyperchaotic map with homogenous multistability

“…Chaos plays an important role in image encryption [1][2][3][4][5], secure communication [6][7][8], computer engineering [9][10], and even other fields [11][12]. The discrete chaotic map shows its potential power as a continuous chaotic system.…”