Huan Zhang¹, Kangfeng Zheng^{1, *}, Xiujuan Wang², Shoushan Luo¹, Bin Wu¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 763-786, 2020, DOI:10.32604/cmc.2020.06553

Abstract As a core component of the network, web applications have become one of the preferred targets for attackers because the static configuration of web applications simplifies the exploitation of vulnerabilities by attackers. Although the moving target defense (MTD) has been proposed to increase the attack difficulty for the attackers, there is no solo approach can cope with different attacks; in addition, it is impossible to implement all these approaches simultaneously due to the resource limitation. Thus, the selection of an optimal defense strategy based on MTD has become the focus of research. In general, the… More >

Yanchao Yue^{1, *}, Tangbing Chen¹, Lingling Zhang¹, Moustafa Abdelsalam¹, Josephine Musanyufu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 259-272, 2020, DOI:10.32604/cmes.2020.07218 - 01 January 2020

Abstract Based on wave interference, a methodology to realize the total transmission phenomenon of SH0 waves is proposed in this paper. After a systematical theoretical investigation, an exact frequency of a flat plate consisting of another medium with finite length, is obtained, which is furthermore exemplified by the finite element method. This frequency is the same as the classical Fabry-Perot condition and dependent on the thickness of the material. It has been revealed that an SH0 wave, with its wavelength equal to twice of the length of another medium, can totally transmit across the medium without… More >

Wenyan Guo^{1, *}, Ting Liu¹, Fang Dai¹, Peng Xu¹

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 337-354, 2020, DOI:10.32604/cmc.2020.06411

Abstract Whale optimization algorithm (WOA) is a new population-based metaheuristic algorithm. WOA uses shrinking encircling mechanism, spiral rise, and random learning strategies to update whale’s positions. WOA has merit in terms of simple calculation and high computational accuracy, but its convergence speed is slow and it is easy to fall into the local optimal solution. In order to overcome the shortcomings, this paper integrates adaptive neighborhood and hybrid mutation strategies into whale optimization algorithms, designs the average distance from itself to other whales as an adaptive neighborhood radius, and chooses to learn from the optimal solution… More >

Abdullah Erdal Tümer^1,∗, Aytekin Akku¸s²

Computer Systems Science and Engineering, Vol.34, No.3, pp. 145-150, 2019, DOI:10.32604/csse.2019.34.145

Abstract In this work, a system based on Radial Basis Function Network was developed to estimate Gross Domestic Product per capita. The data set based on 180 academic parameters of 13 Organisation for Economic Co-operation and Development countries was used to verify the effectiveness and accuracy of the proposed method. Gross Domestic Product per capita was studied to be estimated for the first time with academic parameters in this study. The system has been optimized using feature selection method to eliminate unimportant features. Radial Basis Function network results and Radial Basis Function network with feature selection More >

Purvashi Baynath, Sunjiv Soyjaudah, Maleika Heenaye-Mamode Khan

Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 651-661, 2019, DOI:10.31209/2018.100000060

Abstract The goal of this paper is (i) adopt fusion of features (ii) determine the best method of feature selection technique among ant Colony optimisation, artificial bee colony optimisation and genetic algorithm. The experimental results reported that ant colony Optimisation is a promising techniques as feature selection on Keystroke Dynamics as it outperforms in terms of recognition rate for our inbuilt database where the distance between the keys has been considered for the password derivation with recognition rate 97.85%. Finally the results have shown that a small improvement is obtained by fused features, which suggest that More >

Yue Li¹, Guangquan Xu^2,3, Hequn Xian^1,*, Longlong Rao³, Jiangang Shi^4,*

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 637-647, 2019, DOI:10.31209/2019.100000118

Abstract In order to prevent the spread of Android malware and protect privacy information from being compromised, this study proposes a novel multidimensional hybrid features extraction and analysis method for Android malware detection. This method is based primarily on a multidimensional hybrid features vector by extracting the information of permission requests, API calls, and runtime behaviors. The innovation of this study is to extract greater amounts of static and dynamic features information and combine them, that renders the features vector for training completer and more comprehensive. In addition, the feature selection algorithm is used to further More >

Tinghuai Ma^1,*, Honghao Zhou¹, Dongdong Jia¹, Abdullah Al-Dhelaan², Mohammed Al-Dhelaan², Yuan Tian³

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.2, pp. 569-592, 2019, DOI:10.32604/cmes.2019.07758

Abstract Feature selection has been widely used in data mining and machine learning. Its objective is to select a minimal subset of features according to some reasonable criteria so as to solve the original task more quickly. In this article, a feature selection algorithm with local search strategy based on the forest optimization algorithm, namely FSLSFOA, is proposed. The novel local search strategy in local seeding process guarantees the quality of the feature subset in the forest. Next, the fitness function is improved, which not only considers the classification accuracy, but also considers the size of More >

Xuting Duan^1,2,3, Jingyi Wei^1,2,3, Daxin Tian^1,2,3,*, Jianshan Zhou^1,2,3,4, Haiying Xia⁵, Xin Li⁶, Kunxian Zheng^1,2,3

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1117-1128, 2019, DOI:10.32604/cmc.2019.05578

Abstract In vehicle ad-hoc networks (VANETs), the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes significant. Motivated by the self-adaptive paradigm of cellular attractors, this paper regards an individual communication as a cell, so that we can apply the revised attractor selection model to induce each connected vehicle. Aiming at improving the Quality of Service (QoS), we presented the bio-inspired handover decision-making mechanism. In addition, we employ the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) for any vehicle to choose an access network. This More >

Lubna Alhenak¹, Manar Hosny^1,*

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1045-1074, 2019, DOI:10.32604/cmc.2019.08355

Abstract In recent years, the volume of information in digital form has increased tremendously owing to the increased popularity of the World Wide Web. As a result, the use of techniques for extracting useful information from large collections of data, and particularly documents, has become more necessary and challenging. Text clustering is such a technique; it consists in dividing a set of text documents into clusters (groups), so that documents within the same cluster are closely related, whereas documents in different clusters are as different as possible. Clustering depends on measuring the content (i.e., words) of… More >

Mamouni El Mamoun^1,*, Zennaki Mahmoud¹, Sadouni Kaddour¹

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 995-1008, 2019, DOI:10.32604/cmc.2019.08081

Abstract Using Support Vector Machine (SVM) requires the selection of several parameters such as multi-class strategy type (one-against-all or one-against-one), the regularization parameter C, kernel function and their parameters. The choice of these parameters has a great influence on the performance of the final classifier. This paper considers the grid search method and the particle swarm optimization (PSO) technique that have allowed to quickly select and scan a large space of SVM parameters. A comparative study of the SVM models is also presented to examine the convergence speed and the results of each model. SVM is More >