Mixed-strategy game based trust management for clustered wireless sensor networks

Dong Hao, Avishek Adhikari, Kouichi Sakurai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)


Wireless sensor networks are vulnerable to a large number of security threats and malicious attacks. The traditional security approaches from encryption and authentication are insufficient to defend the insider attacks which are launched inside of the WSNs and bypass the crypto-based defence. Trust management has been recently suggested as one of the effective security mechanisms for distributed systems, and is a promising new approach to solve the security challenges in wireless sensor networks. However, to the best of our knowledge, it is still a challenge to establish an integrated trust management mechanism with comprehensive security analysis. In this paper, we consider the clustered wireless sensor network in which the cluster head is in charge of the trust management of other sensor nodes. We propose a novel, integrated trust management mechanism for the cluster wireless sensor networks, and analyze the optimal decision making policy by using game theory. First, the upstream/downstream joint monitoring scheme is implemented to securely and efficiently observe the behavior of the insider nodes. Then based on the monitoring results, the local trustworthiness and global trust worthiness are derived based on the trust exchange and the trust computation. Finally, by game theoretic analysis of the security interaction between the attacker and the network, the optimal trust policy can be made based on min-max rule, and the optimal utility of the WSNs can be guaranteed.

Original languageEnglish
Title of host publicationTrusted Systems - Third International Conference, INTRUST 2011, Revised Selected Papers
Number of pages19
Publication statusPublished - 2012
Event3rd International Conference on Trusted Systems, INTRUST 2011 - Beijing, China
Duration: Nov 27 2011Nov 29 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7222 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other3rd International Conference on Trusted Systems, INTRUST 2011

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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