DANTD: A Deep Abnormal Network Traffic Detection Model for Security of Industrial Internet of Things Using High-order Features

With the development of blockchain, artificial intelligence and data mining technology, abnormal network traffic data has become easy to obtain. The traffic detection model detects the traffic patterns in the network to find abnormal traffic that does not conform to the normal traffic law, which has...

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Veröffentlicht in:	IEEE internet of things journal 2023-12, Vol.10 (24), p.1-1
Hauptverfasser:	Shi, Guolong, Shen, Xinyi, Xiao, Fuke, He, Yigang
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Brain modeling Communications traffic Computational modeling Convolutional Neural Networks Cryptography Cybersecurity Data augmentation Data mining Data models Detection Model Feature extraction Generative Adversarial Networks Industrial applications Industrial Internet of Things Internet of Things Predictive models Security Traffic models
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