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  • Open Access

    ARTICLE

    A Secure Framework for WSN-IoT Using Deep Learning for Enhanced Intrusion Detection

    Chandraumakantham Om Kumar1,*, Sudhakaran Gajendran2, Suguna Marappan1, Mohammed Zakariah3, Abdulaziz S. Almazyad4

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 471-501, 2024, DOI:10.32604/cmc.2024.054966 - 15 October 2024

    Abstract The security of the wireless sensor network-Internet of Things (WSN-IoT) network is more challenging due to its randomness and self-organized nature. Intrusion detection is one of the key methodologies utilized to ensure the security of the network. Conventional intrusion detection mechanisms have issues such as higher misclassification rates, increased model complexity, insignificant feature extraction, increased training time, increased run time complexity, computation overhead, failure to identify new attacks, increased energy consumption, and a variety of other factors that limit the performance of the intrusion system model. In this research a security framework for WSN-IoT, through… More >

  • Open Access

    ARTICLE

    Modeling Target Detection and Performance Analysis of Electronic Countermeasures for Phased Radar

    T. Jagadesh1,2, B. Sheela Rani3,*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 449-463, 2023, DOI:10.32604/iasc.2023.026868 - 06 June 2022

    Abstract Interference is a key factor in radar return misdetection. Strong interference might make it difficult to detect the signal or targets. When interference occurs in the sidelobes of the antenna pattern, Sidelobe Cancellation (SLC) and Sidelobe Blanking are two unique solutions to solve this problem (SLB). Aside from this approach, the probability of false alert and likelihood of detection are the most essential parameters in radar. The chance of a false alarm for any radar system should be minimal, and as a result, the probability of detection should be high. There are several interference cancellation… More >

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