A novel method of S-box design based on discrete chaotic maps and cuckoo search algorithm

2020 ◽  
Author(s):  
Hussam S. Alhadawi ◽  
Mazlina Abdul Majid ◽  
Dragan Lambić ◽  
Musheer Ahmad
Keyword(s):  
Chaotic Maps ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Novel Method

scholarly journals Modified Cuckoo Search Algorithm: A Novel Method to Minimize the Fuel Cost

Energies ◽  
2018 ◽  
Vol 11 (6) ◽  
pp. 1328 ◽  
Author(s):  
Thang Nguyen ◽  
Dieu Vo ◽  
Nguyen Vu Quynh ◽  
Le Van Dai
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Fuel Cost ◽  
Novel Method

scholarly journals Cuckoo Search Algorithm with Chaotic Maps

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Lijin Wang ◽  
Yiwen Zhong
Keyword(s):  
Random Walk ◽  
Chaotic Maps ◽  
Search Algorithm ◽  
Optimization Technique ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Scaling Factor ◽  
Convergence Speed ◽  
Solution Quality ◽  
Two Parameters

Cuckoo search algorithm is a novel nature-inspired optimization technique based on the obligate brood parasitic behavior of some cuckoo species. It iteratively employs Lévy flights random walk with a scaling factor and biased/selective random walk with a fraction probability. Unfortunately, these two parameters are used in constant value schema, resulting in a problem sensitive to solution quality and convergence speed. In this paper, we proposed a variable value schema cuckoo search algorithm with chaotic maps, called CCS. In CCS, chaotic maps are utilized to, respectively, define the scaling factor and the fraction probability to enhance the solution quality and convergence speed. Extensive experiments with different chaotic maps demonstrate the improvement in efficiency and effectiveness.

scholarly journals A Novel adaptative Discrete Cuckoo Search Algorithm for parameter optimization in computer vision

2017 ◽  
Vol 20 (60) ◽  
pp. 51 ◽  
Author(s):  
Loubna Benchikhi ◽  
Mohamed Sadgal ◽  
Aziz Elfazziki ◽  
Fatimaezzahra Mansouri
Keyword(s):  
Computer Vision ◽  
Parameter Optimization ◽  
Expert Knowledge ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Novel Approach ◽  
Novel Method ◽  
Computer Vision Applications ◽  
Must Experiment

Computer vision applications require choosing operators and their parameters, in order to provide the best outcomes. Often, the users quarry on expert knowledge and must experiment many combinations to find manually the best one. As performance, time and accuracy are important, it is necessary to automate parameter optimization at least for crucial operators. In this paper, a novel approach based on an adaptive discrete cuckoo search algorithm (ADCS) is proposed. It automates the process of algorithms’ setting and provides optimal parameters for vision applications. This work reconsiders a discretization problem to adapt the cuckoo search algorithm and presents the procedure of parameter optimization. Some experiments on real examples and comparisons to other metaheuristic-based approaches: particle swarm optimization (PSO), reinforcement learning (RL) and ant colony optimization (ACO) show the efficiency of this novel method.

scholarly journals Detection of copy-move image forgery using SVD and cuckoo search algorithm

2018 ◽  
Vol 7 (2.13) ◽  
pp. 79 ◽  
Author(s):  
Abhishek Kashyap ◽  
Megha Agarwal ◽  
Hariom Gupta
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Forgery Detection ◽  
Single Value Decomposition ◽  
Novel Method ◽  
Block Based ◽  
Copy Move Forgery Detection ◽  
Value Decomposition ◽  
Parameter Values

Copy-move Copy move forgery (CMF) is one of the straightforward strategies to create forged images. To detect this kind of forgery one of the widely used method is single value decomposition (SVD). Few methods based on SVD are most acceptable but some methods are less acceptable because these methods highly depend on those parameters value, which is manually selected depending upon the tampered images. For different images, we require different parameter values. In this paper, we have proposed a novel method, which uses both copy-move forgery detection using SVD and Cuckoo search (CS) algorithm. It utilizes Cuckoo search algorithm to generate customized parameter values for different tampered images, which are used in copy-move forgery detection (CMFD) under block based framework. 

scholarly journals Robust Video Watermarking using Secret Sharing and Cuckoo Search Algorithm

2019 ◽  
Vol 8 (11) ◽  
pp. 1893-1901
Keyword(s):  
Secret Sharing ◽  
Search Algorithm ◽  
Fitness Function ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Video Watermarking ◽  
Computational Time ◽  
Transform Domain ◽  
Optimization Function ◽  
Novel Method

Cuckoo search algorithm is an efficiently designed algorithm for optimization based on the behavior of blood parasitism of Cuckoo species. The main advantages of Cuckoo Search algorithm are its simplicity, less computational time and efficiency. With said advantages, a novel method on video watermarking using Cuckoo search algorithm in DWT-SVD transform domain is proposed. SSIM, BER are used for fitness function in optimization function. The method proposed uses secret share method to achieve more security of watermark. The experimental results prove that the proposed video watermarking method provides good imperceptibility and more robust to attacks compared to few related methods

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

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