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  • Open Access

    ARTICLE

    Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks

    Fei Li1, *, Jiayan Zhang1, Edward Szczerbicki2, Jiaqi Song1, Ruxiang Li 1, Renhong Diao1

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 653-681, 2020, DOI:10.32604/cmc.2020.011264 - 23 July 2020

    Abstract The increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated the intrusion detection system based on the in-vehicle system. We combined two algorithms to realize the efficient learning of the vehicle’s boundary behavior and the detection of intrusive behavior. In order to More >

  • Open Access

    ARTICLE

    A Multi Criterion Fuzzy Based Energy Efficient Routing Protocol for Ad hoc Networks

    Geetha N., Sankar A.

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 711-719, 2018, DOI:10.1080/10798587.2017.1309003

    Abstract The routing protocol for an ad hoc network should be efficient in utilizing the available resources to prolong the network lifetime. A Multi Criterion Fuzzy based Energy Efficient Routing Protocol (MCFEER) for Ad hoc Networks selects the path on constraints like bandwidth, battery life, hop count and buffer occupancy. In the route discovery phase, fuzzy system is applied for optimal route selection by destination node leading to successful data transmission. Multiple stable paths are preserved in route cache for usage during the route maintenance phase. The results are competitive when compared with Power aware Energy More >

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