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  • Open Access

    ARTICLE

    Optimal Hybrid Deep Learning Enabled Attack Detection and Classification in IoT Environment

    Fahad F. Alruwaili*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 99-115, 2023, DOI:10.32604/cmc.2023.034752

    Abstract The Internet of Things (IoT) paradigm enables end users to access networking services amongst diverse kinds of electronic devices. IoT security mechanism is a technology that concentrates on safeguarding the devices and networks connected in the IoT environment. In recent years, False Data Injection Attacks (FDIAs) have gained considerable interest in the IoT environment. Cybercriminals compromise the devices connected to the network and inject the data. Such attacks on the IoT environment can result in a considerable loss and interrupt normal activities among the IoT network devices. The FDI attacks have been effectively overcome so far by conventional threat detection… More >

  • Open Access

    ARTICLE

    Coot Optimization with Deep Learning-Based False Data Injection Attack Recognition

    T. Satyanarayana Murthy1, P. Udayakumar2, Fayadh Alenezi3, E. Laxmi Lydia4, Mohamad Khairi Ishak5,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 255-271, 2023, DOI:10.32604/csse.2023.034193

    Abstract The recent developments in smart cities pose major security issues for the Internet of Things (IoT) devices. These security issues directly result from inappropriate security management protocols and their implementation by IoT gadget developers. Cyber-attackers take advantage of such gadgets’ vulnerabilities through various attacks such as injection and Distributed Denial of Service (DDoS) attacks. In this background, Intrusion Detection (ID) is the only way to identify the attacks and mitigate their damage. The recent advancements in Machine Learning (ML) and Deep Learning (DL) models are useful in effectively classifying cyber-attacks. The current research paper introduces a new Coot Optimization Algorithm… More >

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