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Adaptive Defending Strategy for Smart Grid Attacks

Authors:

Jianye Hao,

Eunsuk Kang,

Daniel Jackson,

Jun SunAuthors Info & Claims

SEGS '14: Proceedings of the 2nd Workshop on Smart Energy Grid Security

Pages 23 - 30

https://doi.org/10.1145/2667190.2667195

Published: 07 November 2014 Publication History

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Abstract

One active area of research in smart grid security focuses on applying game-theoretic frameworks to analyze interactions between a system and an attacker and formulate effective defense strategies. In previous work, a Nash equilibrium (NE) solution is chosen as the optimal defense strategy, which [7, 9] implies that the attacker has complete knowledge of the system and would also employ the corresponding NE strategy. In practice, however, the attacker may have limited knowledge and resources, and thus employ an attack which is less than optimal, allowing the defender to devise more efficient strategies.

We propose a novel approach called an adaptive Markov Strategy (AMS) for defending a system against attackers with unknown, dynamic behaviors. The algorithm for computing an AMS is theoretically guaranteed to converge to a best response strategy against any stationary attacker, and also converge to a Nash equilibrium if the attacker is sufficiently intelligent to employ the AMS to launch the attack. To evaluate the effectiveness of an AMS in smart grid systems, we study a class of data integrity attacks that involve injecting false voltage information into a substation, with the goal of causing load shedding (and potentially a blackout). Our preliminary results show that the amount of load shedding costs can be significantly reduced by employing an AMS over a NE strategy.

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Cited By

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Boudko SAbie H(2019)Adaptive Cybersecurity Framework for Healthcare Internet of Things2019 13th International Symposium on Medical Information and Communication Technology (ISMICT)10.1109/ISMICT.2019.8743905(1-6)Online publication date: May-2019
https://doi.org/10.1109/ISMICT.2019.8743905
Wang XJi SLiang YLeung HChiu D(2019)An unsupervised strategy for defending against multifarious reputation attacksApplied Intelligence10.1007/s10489-019-01490-949:12(4189-4210)Online publication date: 25-May-2019
https://doi.org/10.1007/s10489-019-01490-9
Guo YGong YNjilla LKamhoua C(2018)A stochastic game approach to cyber-physical security with applications to smart gridIEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)10.1109/INFCOMW.2018.8406833(33-38)Online publication date: Apr-2018
https://doi.org/10.1109/INFCOMW.2018.8406833
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Adaptive Defending Strategy for Smart Grid Attacks

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Published In

SEGS '14: Proceedings of the 2nd Workshop on Smart Energy Grid Security

November 2014

60 pages

ISBN:9781450331548

DOI:10.1145/2667190

General Chairs:
Klaus Kursawe
ENCS, The Netherlands
,
Benessa Defend
ENCS, The Netherlands
,
Program Chair:
Klaus Kursawe
ENCS, The Netherlands

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

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Published: 07 November 2014

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CCS'14

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SIGSAC

CCS'14: 2014 ACM SIGSAC Conference on Computer and Communications Security

November 7, 2014

Arizona, Scottsdale, USA

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SEGS '14 Paper Acceptance Rate 7 of 11 submissions, 64%;

Overall Acceptance Rate 19 of 38 submissions, 50%

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CCS '24

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ACM SIGSAC Conference on Computer and Communications Security

October 14 - 18, 2024

Salt Lake City , UT , USA

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Boudko SAbie H(2019)Adaptive Cybersecurity Framework for Healthcare Internet of Things2019 13th International Symposium on Medical Information and Communication Technology (ISMICT)10.1109/ISMICT.2019.8743905(1-6)Online publication date: May-2019
https://doi.org/10.1109/ISMICT.2019.8743905
Wang XJi SLiang YLeung HChiu D(2019)An unsupervised strategy for defending against multifarious reputation attacksApplied Intelligence10.1007/s10489-019-01490-949:12(4189-4210)Online publication date: 25-May-2019
https://doi.org/10.1007/s10489-019-01490-9
Guo YGong YNjilla LKamhoua C(2018)A stochastic game approach to cyber-physical security with applications to smart gridIEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)10.1109/INFCOMW.2018.8406833(33-38)Online publication date: Apr-2018
https://doi.org/10.1109/INFCOMW.2018.8406833
Kozlov MMalashenko YNazarova INovikova N(2017)Fuel and energy system control at large-scale damages. 1. Network model and software implementationJournal of Computer and Systems Sciences International10.1134/S106423071706009056:6(945-968)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1134/S1064230717060090

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A game theory based optimal allocation strategy for defense resources of smart grid under cyber-attack

Defending against flooding-based distributed denial-of-service attacks: a tutorial

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A game theory based optimal allocation strategy for defense resources of smart grid under cyber-attack

Defending against flooding-based distributed denial-of-service attacks: a tutorial

Strategy-Aware Mitigation Using Markov Games for Dynamic Application-Layer Attacks

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