Cryptanalysis of a colour image encryption using chaotic APFM nonlinear adaptive filter

Fan, Hui; Li, Ming; Dong, Liyun; Zhang, En

doi:10.1016/j.sigpro.2017.08.018

Cited by 35 publications

(12 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The traditional method is difficult to solve these problems, so the intelligent algorithms are required to solve these problems. Inspired by nature, these strong metaheuristic algorithms are applied to solve NP-hard problems such as scheduling [3][4][5][6][7], image [8][9][10], feature selection [11][12][13] and detection [14][15][16], path planning [17,18], cyber-physical social system [19,20], texture discrimination [21], factor evaluation [22], saliency detection [23], classification [24,25], object extraction [26], gesture segmentation [27], economic load dispatch [28,29], shape design [30], big data and large-scale optimization [31][32][33], signal processing [34], silencing efficacy prediction [35], multi-objective optimization [36,37], unit commitment [38,39], vehicle routing [40], knapsack problem [41][42][43] and fault diagnosis [44][45][46], and test-sheet composition…”

Section: Introductionmentioning

confidence: 99%

Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem

Jiāng¹,

Li-hong²,

Li³

et al. 2021

IJCIS

View full text Add to dashboard Cite

The permutation flow shop scheduling problem (PFSSP) is a typical production scheduling problem and it has been proved to be a nondeterministic polynomial (NP-hard) problem when its scale is larger than 3. The whale optimization algorithm (WOA) is a new swarm intelligence algorithm which performs well for PFSSP. But the stability is still low, and the optimization results are not too good. On this basis, we optimize the parameters of WOA through chaos theory, and put forward a chaotic whale algorithm (CWA). Firstly, in this paper, the proposed CWA is combined with Nawaz-Ensco-Ham (NEH) and largest-rank-value (LRV) rule to initialize the population. Next, chaos theory is applied to WOA algorithm to improve its convergence speed and stability. On this basis, we also use cross operator and reversal-insertion operator to enhance the search ability of the algorithm. Finally, the improved local search algorithm is used to optimize the job sequence to find the minimum makespan. In several experiments, different benchmarks are used to investigate the performance of CWA. The experimental results show that CWA has better performance than other scheduling algorithms.

show abstract

Section: Introductionmentioning

confidence: 99%

Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem

Jiāng¹,

Li-hong²,

Li³

et al. 2021

IJCIS

View full text Add to dashboard Cite

show abstract

“…Optimization problems have been one of the most important research topics in recent years. They exist in many domains, such as scheduling [1,2], image processing [3][4][5][6], feature selection [7][8][9] and detection [10], path planning [11,12], feature selection [13], cyber-physical social system [14,15], texture discrimination [16], saliency detection [17], classification [18,19], object extraction [20], shape design [21], big data and large-scale optimization [22,23], multi-objective optimization [24], knapsack problem [25][26][27], fault diagnosis [28][29][30], and test-sheet composition [31]. Metaheuristic algorithms [32], a theoretical tool, are based on nature-inspired ideas, which have been extensively used to solve highly non-linear complex multi-objective optimization problems [33][34][35].…”

Section: Introductionmentioning

confidence: 99%

“…DMQL-CS Algorithm. Input: Population size, NP; Maximum number of function evaluations, MAX_FES, LP (1) Randomly initialize position of NP nest, FES = NP;(2) Calculate the fitness value of each initial solution;(3) while (stopping criterion is not meet do)(4) Select the best step size control strategy according to Algorithm 2;(5) Generate new solution x t+1 i with the new step size by Lévy flights;(6) …”

mentioning

confidence: 99%

Using Cuckoo Search Algorithm with Q-Learning and Genetic Operation to Solve the Problem of Logistics Distribution Center Location

Xiao

Lei

et al. 2020

Mathematics

View full text Add to dashboard Cite

Cuckoo search (CS) algorithm is a novel swarm intelligence optimization algorithm, which is successfully applied to solve some optimization problems. However, it has some disadvantages, as it is easily trapped in local optimal solutions. Therefore, in this work, a new CS extension with Q-Learning step size and genetic operator, namely dynamic step size cuckoo search algorithm (DMQL-CS), is proposed. Step size control strategy is considered as action in DMQL-CS algorithm, which is used to examine the individual multi-step evolution effect and learn the individual optimal step size by calculating the Q function value. Furthermore, genetic operators are added to DMQL-CS algorithm. Crossover and mutation operations expand search area of the population and improve the diversity of the population. Comparing with various CS algorithms and variants of differential evolution (DE), the results demonstrate that the DMQL-CS algorithm is a competitive swarm algorithm. In addition, the DMQL-CS algorithm was applied to solve the problem of logistics distribution center location. The effectiveness of the proposed method was verified by comparing with cuckoo search (CS), improved cuckoo search algorithm (ICS), modified chaos-enhanced cuckoo search algorithm (CCS), and immune genetic algorithm (IGA) for both 6 and 10 distribution centers.

show abstract

“…Wang et al [62] crypt-analyzed the Chanil Pak scheme [23] using a chosen plaintext attack [63]. H. Fan et al [64] exploited the weakness in the encryption scheme proposed by H. I. Hsiao [25] using the chosen-plaintext attack while R. Rhouma et al [65] break the cipher presented by V. Patidar [58] using the same technique to recover the original image without knowing the secret key. Similarly, X. Zhang [66] cryptanalyzed the Y. Liu [59] designed technique using a chosen plaintext attack.…”

Section: Introductionmentioning

confidence: 99%

A Color Image Encryption Algorithm Based on One Time Key, Chaos Theory, and Concept of Rotor Machine

et al. 2020

View full text Add to dashboard Cite

An innovative method proposed for encrypting color images is comprised of one-time keys and chaos theory using a distinctive concept of rotor machine. The novelty of this scheme is that the rows and columns of 2-dimensional images are converted into circular object called rotor and can be rotated at 360 degrees in clockwise or anti clockwise direction. The rotation will change the existing rotor into new one and can be used in substitution process of plain image. This process can be repeated β times and each time a new rotor is created just by a simple rotation. The rotation is performed in terms of pixels so degree of angle is converted into number of pixels. Using this method, same object with new face (after rotation) is used for encryption. The pixels of color image are permuted using the sorted index of logistic sequence. Then, three pseudo-random images are created from Piecewise Linear Chaotic Map (PWLCM). For substitution, both the permuted color channels and pseudo-random images are transformed into rotors. The angle is obtained from Chen chaotic system. The one-time keys are for chaotic maps are generated by using 512-bits hash of plain image. The simulated outcomes demonstrate that the proposed system has high quality of results and requires only single round of encryption to achieve high encryption along with high robustness against the transmission noises.

show abstract

Cryptanalysis of a colour image encryption using chaotic APFM nonlinear adaptive filter

Cited by 35 publications

References 24 publications

Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem

Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem

Using Cuckoo Search Algorithm with Q-Learning and Genetic Operation to Solve the Problem of Logistics Distribution Center Location

A Color Image Encryption Algorithm Based on One Time Key, Chaos Theory, and Concept of Rotor Machine

Contact Info

Product

Resources

About