NDLI: A Mutual Evaluation Based Trust Management Method for Wireless Sensor Networks

Content Provider	IET Digital Library
Author	Guo, Jingjing Ma, Jianfeng Wan, Tao
Abstract	We propose a lightweight trust system for the clustered wireless sensor networks based on the mutual evaluation between the cluster heads and sensor nodes. We evaluate the trust level of a cluster head in two aspects, namely, trust level as a service provider and a supervisor. We consider multidimensional trust attributes to compute the global trust value of a node. By means of the Petri net (PN), we illustrate the performance of an entity in our trust model. Theoretical analyses as well as simulations are done and the results showed that our model with linear computational complexity had less memory and communication overhead when compared with the current state-of-art trust management scheme. In addition, our model can detect malicious and selfish entities (especially the malicious cluster head) and resist various attacks efficiently.
Starting Page	407
Ending Page	415
Page Count	9
ISSN	10224653
Volume Number	26
e-ISSN	20755597
Issue Number	Issue 2, Mar (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/cje/26/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/cje.2017.01.012
Journal	Chinese Journal of Electronics
Publisher Date	2017-03-01
Access Restriction	Open
Rights Holder	© Chinese Institute of Electronics
Subject Keyword	Clustered Wireless Sensor Network Combinatorial Mathematics Computational Complexity Global Trust Value Lightweight Trust System Linear Computational Complexity Malicious Cluster Head Malicious Detection Multidimensional Trust Attributes Mutual Evaluation Network Management Petri Net Petri Nets Selfish Entity Detection Sensor Node Service Provider Telecommunication Network Management Telecommunication Security Trust Management Method Wireless Sensor Network
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering

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