Influence of DoS attacks on intrusion detection systems

Titorenko, Aleksey A.; Goncharov, Dmitry E.

doi:10.1109/eiconrus.2018.8317050

Cited by 3 publications

(1 citation statement)

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“…The protocol in [20] used game means to determine whether to enable IDS (intrusion detection systems) to reduce the resource consumption caused by IDS. Literature [21] calculates the benefits according to the statistics data in the specific network environment to improve the performance and fault tolerance. But the author did not give the data statistics method.…”

Section: Introductionmentioning

confidence: 99%

Research on Detection and Defense Mechanisms of DoS Attacks Based on BP Neural Network and Game Theory

Gao

Zhang

et al. 2019

IEEE Access

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DoS (Denial of Service) attacks are becoming one of the most serious security threats to global networks. We analyze the existing DoS detection methods and defense mechanisms in depth. In this paper, BP (back propagation) neural networks and game theory are introduced to design detection methods and defense mechanisms for the DoS attacks. The BP neural network DoS attacks detection model uses KDDCUP99 as the dataset and selects multiple feature vectors from the dataset that can efficiently identify DoS attacks by large-scale training, which improves the accuracy of detecting DoS attacks to 99.977%. Furthermore, we use game theory to perform secondary analysis on DoS attacks that are not recognized by the neural network model, so that the detection rate of Dos attacks increases from 99.97% to 99.998%. Finally, we propose a DoS attacks defense strategy based on game theory. The simulation results show that the proposed detection method and defense strategy are effective for DoS attacks.

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Section: Introductionmentioning

confidence: 99%