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  • Open Access

    ARTICLE

    CL2ES-KDBC: A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

    Talal Albalawi, P. Ganeshkumar*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3511-3528, 2024, DOI:10.32604/cmc.2024.046396

    Abstract The Internet of Things (IoT) is a growing technology that allows the sharing of data with other devices across wireless networks. Specifically, IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks. In this framework, a Covariance Linear Learning Embedding Selection (CL2ES) methodology is used at first to extract the features highly associated with the IoT intrusions. Then, the Kernel Distributed Bayes Classifier (KDBC) is created to forecast attacks based on the probability distribution value precisely. In addition, a… More >

  • Open Access

    REVIEW

    A Survey on Sensor- and Communication-Based Issues of Autonomous UAVs

    Pavlo Mykytyn1,2,*, Marcin Brzozowski1, Zoya Dyka1,2, Peter Langendoerfer1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1019-1050, 2024, DOI:10.32604/cmes.2023.029075

    Abstract The application field for Unmanned Aerial Vehicle (UAV) technology and its adoption rate have been increasing steadily in the past years. Decreasing cost of commercial drones has enabled their use at a scale broader than ever before. However, increasing the complexity of UAVs and decreasing the cost, both contribute to a lack of implemented security measures and raise new security and safety concerns. For instance, the issue of implausible or tampered UAV sensor measurements is barely addressed in the current research literature and thus, requires more attention from the research community. The goal of this survey is to extensively review… More >

  • Open Access

    ARTICLE

    Modelling an Efficient URL Phishing Detection Approach Based on a Dense Network Model

    A. Aldo Tenis*, R. Santhosh

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2625-2641, 2023, DOI:10.32604/csse.2023.036626

    Abstract The social engineering cyber-attack is where culprits mislead the users by getting the login details which provides the information to the evil server called phishing. The deep learning approaches and the machine learning are compared in the proposed system for presenting the methodology that can detect phishing websites via Uniform Resource Locator (URLs) analysis. The legal class is composed of the home pages with no inclusion of login forms in most of the present modern solutions, which deals with the detection of phishing. Contrarily, the URLs in both classes from the login page due, considering the representation of a real… More >

  • Open Access

    ARTICLE

    A Cyber-Attack Detection System Using Late Fusion Aggregation Enabled Cyber-Net

    P. Shanmuga Prabha*, S. Magesh Kumar

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3101-3119, 2023, DOI:10.32604/iasc.2023.034885

    Abstract Today, securing devices connected to the internet is challenging as security threats are generated through various sources. The protection of cyber-physical systems from external attacks is a primary task. The presented method is planned on the prime motive of detecting cybersecurity attacks and their impacted parameters. The proposed architecture employs the LYSIS dataset and formulates Multi Variant Exploratory Data Analysis (MEDA) through Principle Component Analysis (PCA) and Singular Value Decomposition (SVD) for the extraction of unique parameters. The feature mappings are analyzed with Recurrent 2 Convolutional Neural Network (R2CNN) and Gradient Boost Regression (GBR) to identify the maximum correlation. Novel… More >

  • Open Access

    ARTICLE

    Hybrid Metaheuristics Feature Selection with Stacked Deep Learning-Enabled Cyber-Attack Detection Model

    Mashael M Asiri1, Heba G. Mohamed2, Mohamed K Nour3, Mesfer Al Duhayyim4,*, Amira Sayed A. Aziz5, Abdelwahed Motwakel6, Abu Sarwar Zamani6, Mohamed I. Eldesouki7

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1679-1694, 2023, DOI:10.32604/csse.2023.031063

    Abstract Due to exponential increase in smart resource limited devices and high speed communication technologies, Internet of Things (IoT) have received significant attention in different application areas. However, IoT environment is highly susceptible to cyber-attacks because of memory, processing, and communication restrictions. Since traditional models are not adequate for accomplishing security in the IoT environment, the recent developments of deep learning (DL) models find beneficial. This study introduces novel hybrid metaheuristics feature selection with stacked deep learning enabled cyber-attack detection (HMFS-SDLCAD) model. The major intention of the HMFS-SDLCAD model is to recognize the occurrence of cyberattacks in the IoT environment. At… 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

    Organizational Data Breach: Building Conscious Care Behavior in Incident Response

    Adlyn Adam Teoh1, Norjihan Binti Abdul Ghani1,*, Muneer Ahmad1, Nz Jhanjhi2, Mohammed A. Alzain3, Mehedi Masud4

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 505-515, 2022, DOI:10.32604/csse.2022.018468

    Abstract Organizational and end user data breaches are highly implicated by the role of information security conscious care behavior in respective incident responses. This research study draws upon the literature in the areas of information security, incident response, theory of planned behaviour, and protection motivation theory to expand and empirically validate a modified framework of information security conscious care behaviour formation. The applicability of the theoretical framework is shown through a case study labelled as a cyber-attack of unprecedented scale and sophistication in Singapore’s history to-date, the 2018 SingHealth data breach. The single in-depth case study observed information security awareness, policy,… More >

  • Open Access

    ARTICLE

    Efficacy of Unconventional Penetration Testing Practices

    Bandar Abdulrhman Bin Arfaj1, Shailendra Mishra2,*, Mohammed Alshehri1

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 223-239, 2022, DOI:10.32604/iasc.2022.019485

    Abstract The financial and confidential cost of cyberattack has presented a significant loss to the organization and government where the privacy of worthless information has become vulnerable to cyber threat. In terms of efforts implemented to avoid this risk, the cyberattack continues to evolve, making the cybersecurity systems weekend. This has necessitated the importance of comprehensive penetration testing, assessment techniques, and tools to analyze and present the currently available unconventional penetration techniques and tactics to test and examine their key features and role in supporting cybersecurity and measure their effectiveness. The importance of cyberspace and its value make it an eminent… More >

  • Open Access

    ARTICLE

    Cyber-Attack Detection and Mitigation Using SVM for 5G Network

    Sulaiman Yousef Alshunaifi, Shailendra Mishra*, Mohammed Alshehri

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 13-28, 2022, DOI:10.32604/iasc.2022.019121

    Abstract 5G technology is widely seen as a game-changer for the IT and telecommunications sectors. Benefits expected from 5G include lower latency, higher capacity, and greater levels of bandwidth. 5G also has the potential to provide additional bandwidth in terms of AI support, further increasing the benefits to the IT and telecom sectors. There are many security threats and organizational vulnerabilities that can be exploited by fraudsters to take over or damage corporate data. This research addresses cybersecurity issues and vulnerabilities in 4G(LTE) and 5G technology. The findings in this research were obtained by using primary and secondary data. Secondary data… More >

  • Open Access

    ARTICLE

    Analysis of Security Testing Techniques

    Omer Bin Tauqeer1, Sadeeq Jan1,*, Alaa Omar Khadidos2, Adil Omar Khadidos3, Fazal Qudus Khan3, Sana Khattak1

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 291-306, 2021, DOI:10.32604/iasc.2021.017260

    Abstract In the past decades, a significant increase has been observed in cyber-attacks on the web-based systems used for financial purposes. Such individual systems often contain security weaknesses, called vulnerabilities that can be exploited for malicious purposes. The exploitation of such vulnerabilities can result in disclosure and manipulation of sensitive data as well as have destructive effects. To protect such systems, security testing is required on a periodic basis. Various detection and assessment techniques have been suggested by developers and researchers to address these security issues. In this paper, we survey the contributions of academia in the field of security testing… More >

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