Abnormal Traffic Detection System Based on Feature Fusion and Sparse Transformer

This paper presents a feature fusion and sparse transformer-based anomalous traffic detection system (FSTDS). FSTDS utilizes a feature fusion network to encode the traffic data sequences and extracting features, fusing them into coding vectors through shallow and deep convolutional networks, followe...

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Vydané v:	Mathematics (Basel) Ročník 12; číslo 11; s. 1643
Hlavní autori:	Zhao, Xinjian, Miao, Weiwei, Yuan, Guoquan, Jiang, Yu, Zhang, Song, Li, Qianmu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.06.2024
Predmet:	anomaly detection Artificial intelligence Chatbots Coding Communications traffic convolutional neural network Data fusion deep encoder Deep learning Feature extraction feature fusion Machine learning Methods Multilayer perceptrons Neural networks Protocol Signal detection (Electronics) sparse transformer Support vector machines Technology application Testing Traffic information Transformers China
ISSN:	2227-7390, 2227-7390
On-line prístup:	Získať plný text
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