Artificial Intelligence

    

Anomalous Payload Detection System Using MUXConv Neural Network with Parameter Optimization

Authors: CholRyong Pak, HakMyong O, HyokChol U, Hun Nam

This paper proposes how to detect malicious network data in effective and accurate way using MUXConv neural network(MUXCNN) with parameter optimization. First of all, in order to increase detection speed, packets are directly entered into the input of MUXCNN without decoding. Next of all, after training MUXCNN with learning data, we judge that its traffic is normal or abnormal. Simulations and experiments show that the proposed abnormal network-detecting system is more efficient in detection and higher in accuracy than the other multi-layer neural networks.

Comments: 7 Pages.

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Submission history

[v1] 2022-11-10 01:32:55

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