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  • Open Access

    ARTICLE

    Analysis of Feature Importance and Interpretation for Malware Classification

    Dong-Wook Kim1, Gun-Yoon Shin1, Myung-Mook Han2, *

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1891-1904, 2020, DOI:10.32604/cmc.2020.010933

    Abstract This study was conducted to enable prompt classification of malware, which was becoming increasingly sophisticated. To do this, we analyzed the important features of malware and the relative importance of selected features according to a learning model to assess how those important features were identified. Initially, the analysis features were extracted using Cuckoo Sandbox, an open-source malware analysis tool, then the features were divided into five categories using the extracted information. The 804 extracted features were reduced by 70% after selecting only the most suitable ones for malware classification using a learning model-based feature selection method called the recursive feature… More >

  • Open Access

    ARTICLE

    Edge-Computing with Graph Computation: A Novel Mechanism to Handle Network Intrusion and Address Spoofing in SDN

    Rashid Amin1, *, Mudassar Hussain2, Mohammed Alhameed3, Syed Mohsan Raza4, Fathe Jeribi3, Ali Tahir3

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1869-1890, 2020, DOI:10.32604/cmc.2020.011758

    Abstract Software Defined Networking (SDN) being an emerging network control model is widely recognized as a control and management platform. This model provides efficient techniques to control and manage the enterprise network. Another emerging paradigm is edge computing in which data processing is performed at the edges of the network instead of a central controller. This data processing at the edge nodes reduces the latency and bandwidth requirements. In SDN, the controller is a single point of failure. Several security issues related to the traditional network can be solved by using SDN central management and control. Address Spoofing and Network Intrusion… More >

  • Open Access

    ARTICLE

    An Improved Binary Search Anti-Collision Protocol for RFID Tag Identification

    Guozhong Dong1, Weizhe Zhang1, 2, *, Sichang Xuan3, Feng Qin4, Haowen Tan5

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1855-1868, 2020, DOI:10.32604/cmc.2020.09919

    Abstract Radio frequency identification (RFID) has been widespread used in massive items tagged domains. However, tag collision increases both time and energy consumption of RFID network. Tag collision can seriously affect the success of tag identification. An efficient anti-collision protocol is very crucially in RFID system. In this paper, an improved binary search anti-collision protocol namely BRTP is proposed to cope with the tag collision concern, which introduces a Bi-response mechanism. In Biresponse mechanism, two groups of tags allowed to reply to the reader in the same slot. According to Bi-response mechanism, the BRTP strengthens the tag identification of RFID network… More >

  • Open Access

    ARTICLE

    Research on Data Extraction and Analysis of Software Defect in IoT Communication Software

    Wenbin Bi1, Fang Yu2, Ning Cao3, Wei Huo3, Guangsheng Cao4, *, Xiuli Han5, Lili Sun6, Russell Higgs7

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1837-1854, 2020, DOI:10.32604/cmc.2020.010420

    Abstract Software defect feature selection has problems of feature space dimensionality reduction and large search space. This research proposes a defect prediction feature selection framework based on improved shuffled frog leaping algorithm (ISFLA).Using the two-level structure of the framework and the improved hybrid leapfrog algorithm's own advantages, the feature values are sorted, and some features with high correlation are selected to avoid other heuristic algorithms in the defect prediction that are easy to produce local The case where the convergence rate of the optimal or parameter optimization process is relatively slow. The framework improves generalization of predictions of unknown data samples… More >

  • Open Access

    ARTICLE

    Who Will Come: Predicting Freshman Registration Based on Decision Tree

    Lei Yang1, Li Feng1, *, Liwei Tian1, Hongning Dai1

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1825-1836, 2020, DOI:10.32604/cmc.2020.010011

    Abstract The registration rate of freshmen has been a great concern at many colleges and universities, particularly private institutions. Traditionally, there are two inquiry methods: telephone and tuition-payment-status. Unfortunately, the former is not only time-consuming but also suffers from the fact that many students tend to keep their choices secret. On the other hand, the latter is not always feasible because only few students are willing to pay their university tuition fees in advance. It is often believed that it is impossible to predict incoming freshmen’s choice of university due to the large amount of subjectivity. However, if we look at… More >

  • Open Access

    ARTICLE

    Computational Analysis of the Effect of Nano Particle Material Motion on Mixed Convection Flow in the Presence of Heat Generation and Absorption

    Muhammad Ashraf1, Amir Abbas1, Saqib Zia2, Yu-Ming Chu3, 4, Ilyas Khan5, *, Kottakkaran Sooppy Nisar6

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1809-1823, 2020, DOI:10.32604/cmc.2020.011404

    Abstract The present study is concerned with the physical behavior of the combined effect of nano particle material motion and heat generation/absorption due to the effect of different parameters involved in prescribed flow model. The formulation of the flow model is based on basic universal equations of conservation of momentum, energy and mass. The prescribed flow model is converted to non-dimensional form by using suitable scaling. The obtained transformed equations are solved numerically by using finite difference scheme. For the analysis of above said behavior the computed numerical data for fluid velocity, temperature profile, and mass concentration for several constraints that… More >

  • Open Access

    ARTICLE

    APU-D* Lite: Attack Planning under Uncertainty Based on D* Lite

    Tairan Hu1, Tianyang Zhou1, Yichao Zang1, *, Qingxian Wang1, Hang Li2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1795-1807, 2020, DOI:10.32604/cmc.2020.011071

    Abstract With serious cybersecurity situations and frequent network attacks, the demands for automated pentests continue to increase, and the key issue lies in attack planning. Considering the limited viewpoint of the attacker, attack planning under uncertainty is more suitable and practical for pentesting than is the traditional planning approach, but it also poses some challenges. To address the efficiency problem in uncertainty planning, we propose the APU-D* Lite algorithm in this paper. First, the pentest framework is mapped to the planning problem with the Planning Domain Definition Language (PDDL). Next, we develop the pentest information graph to organize network information and… More >

  • Open Access

    ARTICLE

    A Hybrid Path Planning Method Based on Articulated Vehicle Model

    Zhongping Chen1, Dong Wang1, *, Gang Chen2, Yanxi Ren3, Danjie Du4

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1781-1793, 2020, DOI:10.32604/cmc.2020.010902

    Abstract Due to the unique steering mechanism and driving characteristics of the articulated vehicle, a hybrid path planning method based on the articulated vehicle model is proposed to meet the demand of obstacle avoidance and searching the path back and forth of the articulated vehicle. First, Support Vector Machine (SVM) theory is used to obtain the two-dimensional optimal zero potential curve and the maximum margin, and then, several key points are selected from the optimal zero potential curves by using Longest Accessible Path (LAP) method. Next, the Cubic Bezier (CB) curve is adopted to connect the curve that satisfies the curvature… More >

  • Open Access

    ARTICLE

    Tissue Segmentation in Nasopharyngeal CT Images Using TwoStage Learning

    Yong Luo1, Xiaojie Li2, Chao Luo2, Feng Wang1, Xi Wu2, Imran Mumtaz3, Cheng Yi1, *

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1771-1780, 2020, DOI:10.32604/cmc.2020.010069

    Abstract Tissue segmentation is a fundamental and important task in nasopharyngeal images analysis. However, it is a challenging task to accurately and quickly segment various tissues in the nasopharynx region due to the small difference in gray value between tissues in the nasopharyngeal image and the complexity of the tissue structure. In this paper, we propose a novel tissue segmentation approach based on a two-stage learning framework and U-Net. In the proposed methodology, the network consists of two segmentation modules. The first module performs rough segmentation and the second module performs accurate segmentation. Considering the training time and the limitation of… More >

  • Open Access

    ARTICLE

    Secure Provenance of Electronic Records Based on Blockchain

    Qirun Wang1, Fujian Zhu2, Sai Ji2, Yongjun Ren2, *

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1753-1769, 2020, DOI:10.32604/cmc.2020.07366

    Abstract At present, the provenance of electronic records is stored centrally. The centralized way of information storage has huge risks. Whether the database itself is destroyed or the communication between the central database and the external interruption occurs, the provenance information of the stored electronic records will not play its role. At the same time, uncertainties such as fires and earthquakes will also pose a potential threat to centralized databases. Moreover, the existing security provenance model is not specifically designed for electronic records. In this paper, a security provenance model of electronic records is constructed based on PREMIS and METS. Firstly,… More >

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