Title
A Secure Clustering Protocol With Fuzzy Trust Evaluation and Outlier Detection for Industrial Wireless Sensor Networks
Abstract
Security is one of the major concerns in industrial wireless sensor networks (IWSNs). To assure the security in clustered IWSNs, this article presents a secure clustering protocol with fuzzy trust evaluation and outlier detection. First, to deal with the transmission uncertainty in an open wireless medium, an interval type-2 fuzzy logic controller is adopted to estimate the trusts. And then, a density-based outlier detection mechanism is introduced to acquire an adaptive trust threshold used to isolate the malicious nodes from being cluster heads. Finally, a fuzzy-based cluster heads election method is proposed to achieve a balance between energy saving and security assurance, so that a normal sensor node with more residual energy or less confidence on other nodes has higher probability to be the cluster head. Extensive experiments verify that our secure clustering protocol can effectively defend the network against attacks from internal malicious or compromised nodes.
Year
DOI
Venue
2021
10.1109/TII.2020.3019286
IEEE Transactions on Industrial Informatics
Keywords
DocType
Volume
Routing,Protocols,Anomaly detection,Security,Wireless sensor networks,Distributed databases,Cloud computing
Journal
17
Issue
ISSN
Citations 
7
1551-3203
3
PageRank 
References 
Authors
0.39
0
5
Name
Order
Citations
PageRank
Liu Yang1183.80
Yinzhi Lu251.09
Simon X. Yang3218.39
Tan Guo4183.85
Zhifang Liang5123.39