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  • Open Access

    ARTICLE

    Integrated Approach to Detect Cyberbullying Text: Mobile Device Forensics Data

    G. Maria Jones1,*, S. Godfrey Winster2, P. Valarmathie3

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 963-978, 2022, DOI:10.32604/csse.2022.019483

    Abstract Mobile devices and social networks provide communication opportunities among the young generation, which increases vulnerability and cybercrimes activities. A recent survey reports that cyberbullying and cyberstalking constitute a developing issue among youngsters. This paper focuses on cyberbullying detection in mobile phone text by retrieving with the help of an oxygen forensics toolkit. We describe the data collection using forensics technique and a corpus of suspicious activities like cyberbullying annotation from mobile phones and carry out a sequence of binary classification experiments to determine cyberbullying detection. We use forensics techniques, Machine Learning (ML), and Deep Learning (DL) algorithms to exploit suspicious… More >

  • Open Access

    ARTICLE

    Web Security: Emerging Threats and Defense

    Abdulwahed Awad Almutairi1, Shailendra Mishra2,*, Mohammed AlShehri1

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1233-1248, 2022, DOI:10.32604/csse.2022.019427

    Abstract Web applications have become a widely accepted method to support the internet for the past decade. Since they have been successfully installed in the business activities and there is a requirement of advanced functionalities, the configuration is growing and becoming more complicated. The growing demand and complexity also make these web applications a preferred target for intruders on the internet. Even with the support of security specialists, they remain highly problematic for the complexity of penetration and code reviewing methods. It requires considering different testing patterns in both codes reviewing and penetration testing. As a result, the number of hacked… More >

  • Open Access

    ARTICLE

    Identity Governance Framework for Privileged Users

    Mansour Hammoud Alruwies1, Shailendra Mishra2,*, Mohammed Abdul Rahman AlShehri1

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 995-1005, 2022, DOI:10.32604/csse.2022.019355

    Abstract Information technology companies have grown in size and recognized the need to protect their valuable assets. As a result, each IT application has its authentication mechanism, and an employee needs a username and password. As the number of applications increased, as a result, it became increasingly complex to manage all identities like the number of usernames and passwords of an employee. All identities had to be retrieved by users. Both the identities and the access rights associated with those identities had to be protected by an administrator. Management couldn’t even capture such access rights because they couldn’t verify things like… More >

  • Open Access

    ARTICLE

    Network Traffic Prediction Using Radial Kernelized-Tversky Indexes-Based Multilayer Classifier

    M. Govindarajan1,*, V. Chandrasekaran2, S. Anitha3

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 851-863, 2022, DOI:10.32604/csse.2022.019298

    Abstract Accurate cellular network traffic prediction is a crucial task to access Internet services for various devices at any time. With the use of mobile devices, communication services generate numerous data for every moment. Given the increasing dense population of data, traffic learning and prediction are the main components to substantially enhance the effectiveness of demand-aware resource allocation. A novel deep learning technique called radial kernelized LSTM-based connectionist Tversky multilayer deep structure learning (RKLSTM-CTMDSL) model is introduced for traffic prediction with superior accuracy and minimal time consumption. The RKLSTM-CTMDSL model performs attribute selection and classification processes for cellular traffic prediction. In… More >

  • Open Access

    ARTICLE

    Prediction Model for Coronavirus Pandemic Using Deep Learning

    Mamoona Humayun1,*, Ahmed Alsayat2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 947-961, 2022, DOI:10.32604/csse.2022.019288

    Abstract The recent global outbreak of COVID-19 damaged the world health systems, human health, economy, and daily life badly. None of the countries was ready to face this emerging health challenge. Health professionals were not able to predict its rise and next move, as well as the future curve and impact on lives in case of a similar pandemic situation happened. This created huge chaos globally, for longer and the world is still struggling to come up with any suitable solution. Here the better use of advanced technologies, such as artificial intelligence and deep learning, may aid healthcare practitioners in making… More >

  • Open Access

    ARTICLE

    FPD Net: Feature Pyramid DehazeNet

    Shengchun Wang1, Peiqi Chen1, Jingui Huang1,*, Tsz Ho Wong2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1167-1181, 2022, DOI:10.32604/csse.2022.018911

    Abstract We propose an end-to-end dehazing model based on deep learning (CNN network) and uses the dehazing model re-proposed by AOD-Net based on the atmospheric scattering model for dehazing. Compare to the previously proposed dehazing network, the dehazing model proposed in this paper make use of the FPN network structure in the field of target detection, and uses five feature maps of different sizes to better obtain features of different proportions and different sub-regions. A large amount of experimental data proves that the dehazing model proposed in this paper is superior to previous dehazing technologies in terms of PSNR, SSIM, and… More >

  • Open Access

    ARTICLE

    Hybrid Active Contour Mammographic Mass Segmentation and Classification

    K. Yuvaraj*, U. S. Ragupathy

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 823-834, 2022, DOI:10.32604/csse.2022.018837

    Abstract This research implements a novel segmentation of mammographic mass. Three methods are proposed, namely, segmentation of mass based on iterative active contour, automatic region growing, and fully automatic mask selection-based active contour techniques. In the first method, iterative threshold is performed for manual cropped preprocessed image, and active contour is applied thereafter. To overcome manual cropping in the second method, an automatic seed selection followed by region growing is performed. Given that the result is only a few images owing to over segmentation, the third method uses a fully automatic active contour. Results of the segmentation techniques are compared with… More >

  • Open Access

    ARTICLE

    IoT Wireless Intrusion Detection and Network Traffic Analysis

    Vasaki Ponnusamy1, Aun Yichiet1, NZ Jhanjhi2,*, Mamoona humayun3, Maram Fahhad Almufareh3

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 865-879, 2022, DOI:10.32604/csse.2022.018801

    Abstract Enhancement in wireless networks had given users the ability to use the Internet without a physical connection to the router. Almost every Internet of Things (IoT) devices such as smartphones, drones, and cameras use wireless technology (Infrared, Bluetooth, IrDA, IEEE 802.11, etc.) to establish multiple inter-device connections simultaneously. With the flexibility of the wireless network, one can set up numerous ad-hoc networks on-demand, connecting hundreds to thousands of users, increasing productivity and profitability significantly. However, the number of network attacks in wireless networks that exploit such flexibilities in setting and tearing down networks has become very alarming. Perpetrators can launch… More >

  • Open Access

    ARTICLE

    On Vertex-Edge-Degree Topological Descriptors for Certain Crystal Networks

    Sadia Husain1, Fouad A. Abolaban2, Ali Ahmad1, Muhammad Ahsan Asim1, Yasir Ahmad1

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 835-850, 2022, DOI:10.32604/csse.2022.018534

    Abstract Due to the combinatorial nature of graphs they are used easily in pure sciences and social sciences. The dynamical arrangement of vertices and their associated edges make them flexible (like liquid) to attain the shape of any physical structure or phenomenon easily. In the field of ICT they are used to reflect distributed component and communication among them. Mathematical chemistry is another interesting domain of applied mathematics that endeavors to display the structure of compounds that are formed in result of chemical reactions. This area attracts the researchers due to its applications in theoretical and organic chemistry. It also inspires… More >

  • Open Access

    ARTICLE

    Intrusion Detection Systems in Internet of Things and Mobile Ad-Hoc Networks

    Vasaki Ponnusamy1,*, Mamoona Humayun2, N. Z. Jhanjhi3, Aun Yichiet1, Maram Fahhad Almufareh2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1199-1215, 2022, DOI:10.32604/csse.2022.018518

    Abstract Internet of Things (IoT) devices work mainly in wireless mediums; requiring different Intrusion Detection System (IDS) kind of solutions to leverage 802.11 header information for intrusion detection. Wireless-specific traffic features with high information gain are primarily found in data link layers rather than application layers in wired networks. This survey investigates some of the complexities and challenges in deploying wireless IDS in terms of data collection methods, IDS techniques, IDS placement strategies, and traffic data analysis techniques. This paper’s main finding highlights the lack of available network traces for training modern machine-learning models against IoT specific intrusions. Specifically, the Knowledge… More >

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