An Intrusion Detection Algorithm for DDoS Attacks Based on DBN and Three-way Decisions
Yanjie Shen
Abstract
To solve the problems of few DDoS attack detection methods and low intrusion detection rate of existing methods in software defined network (SDN), an intrusion detection algorithm DBN-TWD based on deep belief network (DBN) and Three-way decisions was proposed. Firstly, DBN was used to extract features of SDN flow entries, then directly classifying data in the positive and negative domains, and the data in the boundary domain is reclassified by the K-nearest neighbor algorithm. Simulation results show that compared with other intrusion detection models, the detection rate of this method is higher, and the false alarm rate is lower.
Topics & Concepts
Computer scienceIntrusion detection systemConstant false alarm rateDenial-of-service attackFalse positive rateDeep belief networkData miningArtificial intelligenceAlgorithmThe InternetDeep learningWorld Wide WebNetwork Security and Intrusion DetectionAdvanced Malware Detection TechniquesSoftware-Defined Networks and 5G