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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Bibliographic Details
Published in:	Mathematics (Basel) Vol. 12; no. 11; p. 1643
Main Authors:	Zhao, Xinjian, Miao, Weiwei, Yuan, Guoquan, Jiang, Yu, Zhang, Song, Li, Qianmu
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.06.2024
Subjects:	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
Online Access:	Get full text
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