Traffic Anomaly Detection in Wireless Sensor Networks Based on Principal Component Analysis and Deep Convolution Neural Network

Traffic Anomaly Detection in Wireless Sensor Networks Based on Principal Component Analysis and Deep Convolution Neural Network

With the popularity of wireless networks, wireless sensor networks (WSNs) have advanced rapidly, and their flexibility and ease of deployment have resulted in more security concerns, making it critical to research network intrusion prevention for WSNs. Denial of service (DoS) is a common network att...

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Bibliographic Details
Main Authors: Chengpeng Yao, Yu Yang, Kun Yin, Jinwei Yang
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Wireless sensor networks
denial of service
network attack
principal component analysis
deep convolution neural network
Online Access:https://ieeexplore.ieee.org/document/9903592/

Internet

https://ieeexplore.ieee.org/document/9903592/

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