Packet traffic: a good data source for wireless sensor network modeling and anomaly detection

IEEE Network ◽  
2011 ◽  
Vol 25 (3) ◽  
pp. 15-21 ◽  
Author(s):  
Qinghua Wang
Keyword(s):  
Wireless Sensor Network ◽  
Anomaly Detection ◽  
Sensor Network ◽  
Network Modeling ◽  
Wireless Sensor ◽  
Good Data ◽  
Data Source

Hybrid Anomaly Detection by Using Clustering for Wireless Sensor Network

2018 ◽  
Vol 106 (4) ◽  
pp. 1841-1853 ◽  
Author(s):  
Bilal Ahmad ◽  
Wang Jian ◽  
Zain Anwar Ali ◽  
Sania Tanvir ◽  
M. Sadiq Ali Khan
Keyword(s):  
Wireless Sensor Network ◽  
Anomaly Detection ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Hybrid Anomaly

Anomaly Detection in Wireless Sensor Network

1969 ◽  
Vol 9 (11) ◽  
Author(s):  
Quazi Mamun ◽  
Rafiqul Islam ◽  
Mohammed Kaosar
Keyword(s):  
Wireless Sensor Network ◽  
Anomaly Detection ◽  
Sensor Network ◽  
Wireless Sensor

A Secure Wireless Sensor Network Framework for Manufacturing Monitoring

2010 ◽  
Vol 20-23 ◽  
pp. 249-253
Author(s):  
Yu Xin Mao ◽  
Wen Ya Tian
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Anomaly Detection ◽  
Sensor Network ◽  
Manufacturing Systems ◽  
Point Of View ◽  
Wireless Sensor ◽  
Layered Architecture ◽  
Detection Technology ◽  
Overall Performance

Wireless sensor networks are going to play a more and more important role in applications of next generation manufacturing systems. In this paper, we present a secure and intelligent wireless sensor network framework for manufacturing monitoring. We try to solve the problem of manufacturing monitoring from a new point of view. We introduce the layered architecture of the wireless sensor network framework in detail. Considering the vulnerable feature of Wireless sensor network, we also propose a secure mechanism based on the structure of wireless sensor network by using the anomaly detection technology. The major contribution of this paper is that we integrate wireless sensor network with secure and intelligent technologies to improve the overall performance of manufacturing monitoring.

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