Smart meter data aggregation against wireless attacks: A game-theoretic approach

Yang Cao, Dongliang Duan, Liuqing Yang, Zhi Sun, Haochuan Zhang, Rong Yu

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

2 Scopus citations

Abstract

The efficient design of evolving smart grid faces serious challenges of a variety of malicious attacks. In this paper, the complex decision making processes between a network of electricity users that perform wireless meter data aggregation via other users and multiple sophisticated wireless attackers that are able to act as eavesdroppers and as jammers are investigated. We model the interactions among users and attackers as a hybrid network formation-nonzero sum game. On the one hand, each user seeks to choose the next-hop user that can minimize the electricity use cost which reflects the security and reliability of its meter data transmission. On the other hand, the objective of the attackers is to choose whether to eavesdrop, jam, or use a combination of both strategies, in a way to increase the total network costs. To solve this game, we devised an algorithm based on fictitious play to reach a mixed-strategy Nash equilibrium. Simulation results suggested that the proposed meter data aggregation scheme enables the electricity users to significantly decrease their expected costs as well as adapt to sophisticated wireless attacks in the smart grid.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Communications, ICC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479966646
DOIs
StatePublished - Jul 12 2016
Externally publishedYes
Event2016 IEEE International Conference on Communications, ICC 2016 - Kuala Lumpur, Malaysia
Duration: May 22 2016May 27 2016

Publication series

Name2016 IEEE International Conference on Communications, ICC 2016

Conference

Conference2016 IEEE International Conference on Communications, ICC 2016
Country/TerritoryMalaysia
CityKuala Lumpur
Period5/22/165/27/16

Bibliographical note

Funding Information:
This work is supported by National Natural Science Foundation under Grant #ECCS-1232305 and NSFC under Grant nos. 61422201, 61370159, 61501127 and U1301255.

Publisher Copyright:
© 2016 IEEE.

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