Abstract
This paper explores reliable data fusion in mobile access wireless sensor networks under Byzantine attacks. We consider the q-out-of-m rule, which is popular in distributed detection and can achieve a good tradeoff between the miss detection probability and the false alarm rate. However, a major limitation with it is that the optimal scheme parameters can only be obtained through exhaustive search, making it infeasible for large networks. In this paper, first, by exploiting the linear relationship between the scheme parameters and the network size, we propose simple but effective sub-optimal linear approaches. Second, for better flexibility and scalability, we derive a near-optimal closed-form solution based on the central limit theorem. Third, subjecting to a miss detection constraint, we prove that the false alarm rate of q-out-of-m diminishes exponentially as the network size increases, even if the percentage of malicious nodes remains fixed. Finally, we propose an effective malicious node detection scheme for adaptive data fusion under time-varying attacks; the proposed scheme is analyzed using the entropy-based trust model, and shown to be optimal from the information theory point of view. Simulation examples are provided to illustrate the performance of proposed approaches under both static and dynamic attacks.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IEEE Transactions on Parallel and Distributed Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.