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  • Open Access

    ARTICLE

    A Novel Approach for Network Vulnerability Analysis in IIoT

    K. Sudhakar*, S. Senthilkumar

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 263-277, 2023, DOI:10.32604/csse.2023.029680

    Abstract Industrial Internet of Things (IIoT) offers efficient communication among business partners and customers. With an enlargement of IoT tools connected through the internet, the ability of web traffic gets increased. Due to the raise in the size of network traffic, discovery of attacks in IIoT and malicious traffic in the early stages is a very demanding issues. A novel technique called Maximum Posterior Dichotomous Quadratic Discriminant Jaccardized Rocchio Emphasis Boost Classification (MPDQDJREBC) is introduced for accurate attack detection with minimum time consumption in IIoT. The proposed MPDQDJREBC technique includes feature selection and categorization. First, the network traffic features are collected… More >

  • Open Access

    ARTICLE

    Sammon Quadratic Recurrent Multilayer Deep Classifier for Legal Document Analytics

    Divya Mohan*, Latha Ravindran Nair

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3039-3053, 2022, DOI:10.32604/cmc.2022.024438

    Abstract In recent years, machine learning algorithms and in particular deep learning has shown promising results when used in the field of legal domain. The legal field is strongly affected by the problem of information overload, due to the large amount of legal material stored in textual form. Legal text processing is essential in the legal domain to analyze the texts of the court events to automatically predict smart decisions. With an increasing number of digitally available documents, legal text processing is essential to analyze documents which helps to automate various legal domain tasks. Legal document classification is a valuable tool… More >

  • Open Access

    ARTICLE

    Feature Selection Based on IoT Aware QDA Node Authentication in 5G Networks

    M. P. Haripriya*, P. Venkadesh

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 825-836, 2022, DOI:10.32604/iasc.2022.022940

    Abstract The coming generation in mobile networks is the fifth generation (5G), which appears to be the promoter of the upcoming digital world. 5G is defined by a single piece of cellular access technology or a combination of advanced access technologies. Rather, 5G is a true network assembler that provides consistent support for a slew of novel network topologies. Prior generations provide as a suitable starting point and give support for the security architecture for 5G security. Through authentication and cryptography techniques, many works have tackled the security issues in 3G and 4G networks in an effective manner. However, security of… More >

  • Open Access

    ARTICLE

    Synovial Sarcoma Classification Technique Using Support Vector Machine and Structure Features

    P. Arunachalam1, N. Janakiraman1,*, Arun Kumar Sivaraman2, A. Balasundaram3, Rajiv Vincent2, Sita Rani4, Barnali Dey5, A. Muralidhar2, M. Rajesh2

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1241-1259, 2022, DOI:10.32604/iasc.2022.022573

    Abstract Digital clinical histopathology technique is used for accurately diagnosing cancer cells and achieving optimal results using Internet of Things (IoT) and blockchain technology. The cell pattern of Synovial Sarcoma (SS) cancer images always appeared as spindle shaped cell (SSC) structures. Identifying the SSC and its prognostic indicator are very crucial problems for computer aided diagnosis, especially in healthcare industry applications. A constructive framework has been proposed for the classification of SSC feature components using Support Vector Machine (SVM) with the assistance of relevant Support Vectors (SVs). This framework used the SS images, and it has been transformed into frequency sub-bands… More >

  • Open Access

    ARTICLE

    Research on the Pedestrian Re-Identification Method Based on Local Features and Gait Energy Images

    Xinliang Tang1, Xing Sun1, Zhenzhou Wang1, Pingping Yu1, Ning Cao2, *, Yunfeng Xu3

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1185-1198, 2020, DOI:10.32604/cmc.2020.010283

    Abstract The appearance of pedestrians can vary greatly from image to image, and different pedestrians may look similar in a given image. Such similarities and variabilities in the appearance and clothing of individuals make the task of pedestrian re-identification very challenging. Here, a pedestrian re-identification method based on the fusion of local features and gait energy image (GEI) features is proposed. In this method, the human body is divided into four regions according to joint points. The color and texture of each region of the human body are extracted as local features, and GEI features of the pedestrian gait are also… More >

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