Detecting Blackhole Attack on AODV-based Mobile Ad Hoc Networks by Dynamic Learning Method

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A survey of routing attacks in mobile ad hoc networks (2007, background): “In [ 15 ], the authors analyzed the blackhole attack and showed that a malicious node must increase the destination sequence number sufficiently to convince the source node that the route provided is sufficiently enough.”
DoS Attacks in Mobile Ad Hoc Networks: A Survey (2012, background): “Dynamic Training Method [27] Analyzing differences between sequence numbers of received reply packets False positives”
Dpraodv: A Dyanamic Learning System Against Blackhole Attack in Aodv Based Manet (2009, methodology): “In [4], the feature used is dest_seq_no, which reflects the trend of updating the threshold and hence reflecting the adaptively change in network environment.”
Future Intelligent and Secure Vehicular Network Toward 6G: Machine-Learning Approaches (2020, methodology): “[45], [46] proposed a dynamic attack detection algorithm for AODV routingbased MANET.”
Networking and Communications in Autonomous Driving: A Survey (2019, methodology): “[226] present an anomaly detection scheme based on dynamic training method, which updates the training data periodically.”