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- W4285292783 abstract "Vehicular ad hoc networks (VANETs) are a critical component of intelligent transportation systems (ITS). Because VANET allows the transmission of critical and life-saving information between vehicle nodes, any effort to compromise the network should be recognized immediately, if at all feasible. The distributed denial-of-service (DDoS) assault is one kind of cyber-attack that affects VANET systems’ availability.Akshat Gaurav B.B. Gupta Kwok Tai Chui As a consequence of the DDoS assault, vehicle nodes are unable to transmit vital information. In this context, this experiment proposed edge computing-based DDoS detection techniques. The proposed technique uses packet entropy to distinguish DDoS attack traffic from normal communication. To determine the entropy values, we performed an in-depth study of five different machine learning methods. precision, accuracy, f1 measure, and recall are used to assess the performance of different machine learning methods" @default.
- W4285292783 created "2022-07-14" @default.
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- W4285292783 date "2022-01-01" @default.
- W4285292783 modified "2023-09-25" @default.
- W4285292783 title "Edge Computing-Based DDoS Attack Detection for Intelligent Transportation Systems" @default.
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- W4285292783 doi "https://doi.org/10.1007/978-981-16-8664-1_16" @default.
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