Home / Journals / CSSE / Vol.37, No.1, 2021
  • Open Access

    ARTICLE

    Unified Computational Modelling for Healthcare Device Security Assessment

    Shakeel Ahmed*, Abdulaziz Alhumam
    Computer Systems Science and Engineering, Vol.37, No.1, pp. 1-18, 2021, DOI:10.32604/csse.2021.015775
    Abstract This article evaluates the security techniques that are used to maintain the healthcare devices, and proposes a mathematical model to list these in the order of priority and preference. To accomplish the stated objective, the article uses the Fuzzy Analytic Network Process (ANP) integrated with Technical for Order Preference by Similarities to Ideal Solution (TOPSIS) to find the suitable alternatives of the security techniques for securing the healthcare devices from trespassing. The methodology is enlisted to rank the alternatives/ techniques based on their weights’ satisfaction degree. Thereafter, the ranks of the alternatives determine the order of priority for the techniques… More >

  • Open Access

    ARTICLE

    Comparative Design and Study of A 60 GHz Antenna for Body-Centric Wireless Communications

    Kaisarul Islam1, Tabia Hossain1, Mohammad Monirujjaman Khan1,*, Mehedi Masud2, Roobaea Alroobaea2
    Computer Systems Science and Engineering, Vol.37, No.1, pp. 19-32, 2021, DOI:10.32604/csse.2021.015528
    (This article belongs to this Special Issue: Sensors and Nano-sensors Technologies for Health-Care Applications)
    Abstract In this paper performance of three different designs of a 60 GHz high gain antenna for body-centric communication has been evaluated. The basic structure of the antenna is a slotted patch consisting of a rectangular ring radiator with passive radiators inside. The variation of the design was done by changing the shape of these passive radiators. For free space performance, two types of excitations were used—waveguide port and a coaxial probe. The coaxial probe significantly improved both the bandwidth and radiation efficiency. The center frequency of all the designs was close to 60 GHz with a bandwidth of more than… More >

  • Open Access

    ARTICLE

    Anomaly Detection in ICS Datasets with Machine Learning Algorithms

    Sinil Mubarak1, Mohamed Hadi Habaebi1,*, Md Rafiqul Islam1, Farah Diyana Abdul Rahman, Mohammad Tahir2
    Computer Systems Science and Engineering, Vol.37, No.1, pp. 33-46, 2021, DOI:10.32604/csse.2021.014384
    Abstract An Intrusion Detection System (IDS) provides a front-line defense mechanism for the Industrial Control System (ICS) dedicated to keeping the process operations running continuously for 24 hours in a day and 7 days in a week. A well-known ICS is the Supervisory Control and Data Acquisition (SCADA) system. It supervises the physical process from sensor data and performs remote monitoring control and diagnostic functions in critical infrastructures. The ICS cyber threats are growing at an alarming rate on industrial automation applications. Detection techniques with machine learning algorithms on public datasets, suitable for intrusion detection of cyber-attacks in SCADA systems, as… More >

  • Open Access

    ARTICLE

    Affective State Recognition Using Thermal-Based Imaging: A Survey

    Mustafa M. M. Al Qudah, Ahmad S. A. Mohamed*, Syaheerah L. Lutfi
    Computer Systems Science and Engineering, Vol.37, No.1, pp. 47-62, 2021, DOI:10.32604/csse.2021.015222
    Abstract The thermal-based imaging technique has recently attracted the attention of researchers who are interested in the recognition of human affects due to its ability to measure the facial transient temperature, which is correlated with human affects and robustness against illumination changes. Therefore, studies have increasingly used the thermal imaging as a potential and supplemental solution to overcome the challenges of visual (RGB) imaging, such as the variation of light conditions and revealing original human affect. Moreover, the thermal-based imaging has shown promising results in the detection of psychophysiological signals, such as pulse rate and respiration rate in a contactless and… More >

  • Open Access

    ARTICLE

    A Robust Single-Sensor MPPT Strategy for Shaded Photovoltaic-Battery System

    A. N. M. Alahmadi1, Hegazy Rezk2,3,*
    Computer Systems Science and Engineering, Vol.37, No.1, pp. 63-71, 2021, DOI:10.32604/csse.2021.015029
    Abstract A robust single-sensor global maximum power point tracking (MPPT) strategy based on modern optimization for photovoltaic systems considering shading conditions is proposed in this work. The proposed strategy is designed for battery charging applications and direct current (DC) microgrids. Under normal operation, the curve of photovoltaic (PV) output power versus PV voltage contains only a single peak point. This point can be simply captured using any traditional tracking method like perturb and observe. However, this situation is completely different during the shadowing effect where several peaks appear on the power voltage curve. Most of these peaks are local with only… More >

  • Open Access

    ARTICLE

    Exploring Students Engagement Towards the Learning Management System (LMS) Using Learning Analytics

    Shahrul Nizam Ismail1, Suraya Hamid1,*, Muneer Ahmad1, A. Alaboudi2, Nz Jhanjhi3
    Computer Systems Science and Engineering, Vol.37, No.1, pp. 73-87, 2021, DOI:10.32604/csse.2021.015261
    Abstract Learning analytics is a rapidly evolving research discipline that uses the insights generated from data analysis to support learners as well as optimize both the learning process and environment. This paper studied students’ engagement level of the Learning Management System (LMS) via a learning analytics tool, student’s approach in managing their studies and possible learning analytic methods to analyze student data. Moreover, extensive systematic literature review (SLR) was employed for the selection, sorting and exclusion of articles from diverse renowned sources. The findings show that most of the engagement in LMS are driven by educators. Additionally, we have discussed the… More >

  • Open Access

    ARTICLE

    Layout Optimization for Greenhouse WSN Based on Path Loss Analysis

    Huarui Wu1,2,3, Huaji Zhu1,2,3, Xiao Han1,2,3,*, Wei Xu4
    Computer Systems Science and Engineering, Vol.37, No.1, pp. 89-104, 2021, DOI:10.32604/csse.2021.015030
    Abstract When wireless sensor networks (WSN) are deployed in the vegetable greenhouse with dynamic connectivity and interference environment, it is necessary to increase the node transmit power to ensure the communication quality, which leads to serious network interference. To offset the negative impact, the transmit power of other nodes must also be increased. The result is that the network becomes worse and worse, and node energy is wasted a lot. Taking into account the irregular connection range in the cucumber greenhouse WSN, we measured the transmission characteristics of wireless signals under the 2.4 Ghz operating frequency. For improving network layout in… More >

  • Open Access

    ARTICLE

    TLSmell: Direct Identification on Malicious HTTPs Encryption Traffic with Simple Connection-Specific Indicators

    Zhengqiu Weng1,2, Timing Chen1,*, Tiantian Zhu1, Hang Dong1, Dan Zhou1, Osama Alfarraj3
    Computer Systems Science and Engineering, Vol.37, No.1, pp. 105-119, 2021, DOI:10.32604/csse.2021.015074
    Abstract Internet traffic encryption is a very common traffic protection method. Most internet traffic is protected by the encryption protocol called transport layer security (TLS). Although traffic encryption can ensure the security of communication, it also enables malware to hide its information and avoid being detected. At present, most of the malicious traffic detection methods are aimed at the unencrypted ones. There are some problems in the detection of encrypted traffic, such as high false positive rate, difficulty in feature extraction, and insufficient practicability. The accuracy and effectiveness of existing methods need to be improved. In this paper, we present TLSmell,… More >

  • Open Access

    ARTICLE

    RP-NBSR: A Novel Network Attack Detection Model Based on Machine Learning

    Zihao Shen1,2, Hui Wang1,*, Kun Liu1, Peiqian Liu1, Menglong Ba1, MengYao Zhao3
    Computer Systems Science and Engineering, Vol.37, No.1, pp. 121-133, 2021, DOI:10.32604/csse.2021.014988
    Abstract The rapid progress of the Internet has exposed networks to an increased number of threats. Intrusion detection technology can effectively protect network security against malicious attacks. In this paper, we propose a ReliefF-P-Naive Bayes and softmax regression (RP-NBSR) model based on machine learning for network attack detection to improve the false detection rate and F1 score of unknown intrusion behavior. In the proposed model, the Pearson correlation coefficient is introduced to compensate for deficiencies in correlation analysis between features by the ReliefF feature selection algorithm, and a ReliefF-Pearson correlation coefficient (ReliefF-P) algorithm is proposed. Then, the Relief-P algorithm is used… More >

  • Open Access

    ARTICLE

    A Generative Adversarial Networks for Log Anomaly Detection

    Xiaoyu Duan1, Shi Ying1,*, Wanli Yuan1, Hailong Cheng1, Xiang Yin2
    Computer Systems Science and Engineering, Vol.37, No.1, pp. 135-148, 2021, DOI:10.32604/csse.2021.014030
    Abstract Detecting anomaly logs is a great significance step for guarding system faults. Due to the uncertainty of abnormal log types, lack of real anomaly logs and accurately labeled log datasets. Existing technologies cannot be enough for detecting complex and various log point anomalies by using human-defined rules. We propose a log anomaly detection method based on Generative Adversarial Networks (GAN). This method uses the Encoder-Decoder framework based on Long Short-Term Memory (LSTM) network as the generator, takes the log keywords as the input of the encoder, and the decoder outputs the generated log template. The discriminator uses the Convolutional Neural… More >

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