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  • Open Access

    ARTICLE

    Behavioral Feature and Correlative Detection of Multiple Types of Node in the Internet of Vehicles

    Pengshou Xie1, Guoqiang Ma1, *, Tao Feng1, Yan Yan1, 2, Xueming Han1

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1127-1137, 2020, DOI:10.32604/cmc.2020.09695

    Abstract Undoubtedly, uncooperative or malicious nodes threaten the safety of Internet of Vehicles (IoV) by destroying routing or data. To this end, some researchers have designed some node detection mechanisms and trust calculating algorithms based on some different feature parameters of IoV such as communication, data, energy, etc., to detect and evaluate vehicle nodes. However, it is difficult to effectively assess the trust level of a vehicle node only by message forwarding, data consistency, and energy sufficiency. In order to resolve these problems, a novel mechanism and a new trust calculating model is proposed in this paper. First, the four tuple… More >

  • Open Access

    ARTICLE

    A Distributed Approach of Big Data Mining for Financial Fraud Detection in a Supply Chain

    Hangjun Zhou1, *, Guang Sun1, 2, Sha Fu1, Xiaoping Fan1, Wangdong Jiang1, Shuting Hu1, Lingjiao Li1

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1091-1105, 2020, DOI:10.32604/cmc.2020.09834

    Abstract Supply Chain Finance (SCF) is important for improving the effectiveness of supply chain capital operations and reducing the overall management cost of a supply chain. In recent years, with the deep integration of supply chain and Internet, Big Data, Artificial Intelligence, Internet of Things, Blockchain, etc., the efficiency of supply chain financial services can be greatly promoted through building more customized risk pricing models and conducting more rigorous investment decision-making processes. However, with the rapid development of new technologies, the SCF data has been massively increased and new financial fraud behaviors or patterns are becoming more covertly scattered among normal… More >

  • Open Access

    ARTICLE

    Research on Detection Method of Interest Flooding Attack on Content Centric Network

    Yabin Xu1, 2, 3, *, Ting Xu3, Xiaowei Xu4

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1075-1089, 2020, DOI:10.32604/cmc.2020.09849

    Abstract To improve the attack detection capability of content centric network (CCN), we propose a detection method of interest flooding attack (IFA) making use of the feature of self-similarity of traffic and the information entropy of content name of interest packet. On the one hand, taking advantage of the characteristics of self-similarity is very sensitive to traffic changes, calculating the Hurst index of the traffic, to identify initial IFA attacks. On the other hand, according to the randomness of user requests, calculating the information entropy of content name of the interest packets, to detect the severity of the IFA attack, is.… More >

  • Open Access

    ARTICLE

    Anomaly IoT Node Detection Based on Local Outlier Factor and Time Series

    Fang Wang1, *, Zhe Wei1, Xu Zuo2

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1063-1073, 2020, DOI:10.32604/cmc.2020.09774

    Abstract The heterogeneous nodes in the Internet of Things (IoT) are relatively weak in the computing power and storage capacity. Therefore, traditional algorithms of network security are not suitable for the IoT. Once these nodes alternate between normal behavior and anomaly behavior, it is difficult to identify and isolate them by the network system in a short time, thus the data transmission accuracy and the integrity of the network function will be affected negatively. Based on the characteristics of IoT, a lightweight local outlier factor detection method is used for node detection. In order to further determine whether the nodes are… More >

  • Open Access

    ARTICLE

    Privacy Protection Algorithm for the Internet of Vehicles Based on Local Differential Privacy and Game Model

    Wenxi Han1, 2, Mingzhi Cheng3, *, Min Lei1, 2, Hanwen Xu2, Yu Yang1, 2, Lei Qian4

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1025-1038, 2020, DOI:10.32604/cmc.2020.09815

    Abstract In recent years, with the continuous advancement of the intelligent process of the Internet of Vehicles (IoV), the problem of privacy leakage in IoV has become increasingly prominent. The research on the privacy protection of the IoV has become the focus of the society. This paper analyzes the advantages and disadvantages of the existing location privacy protection system structure and algorithms, proposes a privacy protection system structure based on untrusted data collection server, and designs a vehicle location acquisition algorithm based on a local differential privacy and game model. The algorithm first meshes the road network space. Then, the dynamic… More >

  • Open Access

    ARTICLE

    An Efficient Detection Approach of Content Aware Image Resizing

    Ming Lu1, 2, *, Shaozhang Niu1, Zhenguang Gao3

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 887-907, 2020, DOI:10.32604/cmc.2020.09770

    Abstract Content aware image resizing (CAIR) is an excellent technology used widely for image retarget. It can also be used to tamper with images and bring the trust crisis of image content to the public. Once an image is processed by CAIR, the correlation of local neighborhood pixels will be destructive. Although local binary patterns (LBP) can effectively describe the local texture, it however cannot describe the magnitude information of local neighborhood pixels and is also vulnerable to noise. Therefore, to deal with the detection of CAIR, a novel forensic method based on improved local ternary patterns (ILTP) feature and gradient… More >

  • Open Access

    ARTICLE

    A Comparative Analysis of RAD and Agile Technique for Management of Computing Graduation Projects

    Fazal Qudus Khan1, Saim Rasheed1, Maged Alsheshtawi1, Tarig Mohamed Ahmed1, 2, Sadeeq Jan3, *

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 777-796, 2020, DOI:10.32604/cmc.2020.010959

    Abstract Computing students face the problem with time and quality of the work while managing their graduation/senior projects. Rapid Application Development (RAD) model is based on continual user involvement for the process of requirement gathering via prototyping. After each iteration, the developers can validate the requirements that are completed in the iteration. Managing a project with RAD is easier but not flexible. On the other hand, Agile project management techniques focus on flexibility, agility, teamwork and quality based on user stories. Continual user involvement is avoided, which requires extensive maintenance time for fixing iteration and release of the story points. This… More >

  • Open Access

    ARTICLE

    Performance Anomaly Detection in Web Services: An RNN- Based Approach Using Dynamic Quality of Service Features

    Muhammad Hasnain1, Seung Ryul Jeong2, *, Muhammad Fermi Pasha3, Imran Ghani4

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 729-752, 2020, DOI:10.32604/cmc.2020.010394

    Abstract Performance anomaly detection is the process of identifying occurrences that do not conform to expected behavior or correlate with other incidents or events in time series data. Anomaly detection has been applied to areas such as fraud detection, intrusion detection systems, and network systems. In this paper, we propose an anomaly detection framework that uses dynamic features of quality of service that are collected in a simulated setup. Three variants of recurrent neural networks-SimpleRNN, long short term memory, and gated recurrent unit are evaluated. The results reveal that the proposed method effectively detects anomalies in web services with high accuracy.… More >

  • Open Access

    ARTICLE

    Intelligent Detection Model Based on a Fully Convolutional Neural Network for Pavement Cracks

    Duo Ma1, 2, 3, Hongyuan Fang1, 2, 3, *, Binghan Xue1, 2, 3, Fuming Wang1, 2, 3, Mohammed A. Msekh4, Chiu Ling Chan5

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1267-1291, 2020, DOI:10.32604/cmes.2020.09122

    Abstract The crack is a common pavement failure problem. A lack of periodic maintenance will result in extending the cracks and damage the pavement, which will affect the normal use of the road. Therefore, it is significant to establish an efficient intelligent identification model for pavement cracks. The neural network is a method of simulating animal nervous systems using gradient descent to predict results by learning a weight matrix. It has been widely used in geotechnical engineering, computer vision, medicine, and other fields. However, there are three major problems in the application of neural networks to crack identification. There are too… More >

  • Open Access

    ARTICLE

    Combined molecular docking, homology modeling and DFT method for the modification of bovine serum albumin (BSA) to improve fluorescence spectroscopy for phthalate acid esters chelated with BSA

    MINGHAO LI1, YOULI QIU2, WENHUI ZHANG1, RUIHAO SUN1, MEIJIN DU1, LUZE YANG3, YU LI1,*

    BIOCELL, Vol.44, No.2, pp. 247-255, 2020, DOI:10.32604/biocell.2020.08835

    Abstract While phthalate acid esters (PAEs) cannot fluoresce alone, they can be detected by fluorescence spectroscopy after chelation with bovine serum albumin (BSA). In this study, the types of amino acid residues at the active site of PAEs chelated with BSA were determined using molecular docking technology. A modification scheme of BSA with higher detection sensitivity fluorescence spectroscopy for PAEs was proposed based on the docking results and constructed for a novel BSA structure with a higher detection sensitivity of fluorescence spectroscopy using a homologous modeling method. Density functional theory (DFT) was employed to explore the influence before and after BSA… More >

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