A Framework For Network Intrusion Detection Based on Unsupervised Learning

Anomaly detection is the primary method of detecting intrusion. Unsupervised models, such as auto-encoders network, auto-encoder, and GMM, are currently the most widely used anomaly detection techniques. In reality, the samples used to train the unsupervised model may not be pure enough and may incl...

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Vydané v:	2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) s. 188 - 193
Hlavní autori:	Hui, Wang, Dongming, Wang, Dejian, Li, Lin, Zeng, Zhe, Wang
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 28.05.2021
Predmet:	Conferences Data collection Deep AutoEncoders Network Feature extraction Gaussian Mixture Model(GMM Intrusion Detection System Measurement Network intrusion detection Reconstruction Errors Systems architecture Training
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