TY - GEN
T1 - Power grid defense against malicious cascading failure
AU - Shakarian, Paulo
AU - Lei, Hansheng
AU - Lindelauf, Roy
N1 - Publisher Copyright:
Copyright © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
PY - 2014
Y1 - 2014
N2 - An adversary looking to disrupt a power grid may look to target certain substations and sources of power generation to initiate a cascading failure that maximizes the number of customers without electricity. This is particularly an important concern when the enemy has the capability to launch cyber-attacks as practical concerns (i.e. avoiding disruption of service, presence of legacy systems, etc.) may hinder security. Hence, a defender can harden the security posture at certain power stations but may lack the time and resources to do this for the entire power grid. We model a power grid as a graph and introduce the cascading failure game in which both the defender and attacker choose a subset of power stations such as to minimize (maximize) the number of consumers having access to producers of power. We formalize problems for identifying both mixed and deterministic strategies for both players, prove complexity results under a variety of different scenarios, identify tractable cases, and develop algorithms for these problems. We also perform an experimental evaluation of the model and game on a real-world power grid network. Empirically, we noted that the game favors the attacker as he benefits more from increased resources than the defender. Further, the minimax defense produces roughly the same expected payoff as an easy-to-compute deterministic load based (DLB) defense when played against a minimax attack strategy. However, DLB performs more poorly than minimax defense when faced with the attacker's best response to DLB. This is likely due to the presence of low-load yet high-payoff nodes, which we also found in our empirical analysis.
AB - An adversary looking to disrupt a power grid may look to target certain substations and sources of power generation to initiate a cascading failure that maximizes the number of customers without electricity. This is particularly an important concern when the enemy has the capability to launch cyber-attacks as practical concerns (i.e. avoiding disruption of service, presence of legacy systems, etc.) may hinder security. Hence, a defender can harden the security posture at certain power stations but may lack the time and resources to do this for the entire power grid. We model a power grid as a graph and introduce the cascading failure game in which both the defender and attacker choose a subset of power stations such as to minimize (maximize) the number of consumers having access to producers of power. We formalize problems for identifying both mixed and deterministic strategies for both players, prove complexity results under a variety of different scenarios, identify tractable cases, and develop algorithms for these problems. We also perform an experimental evaluation of the model and game on a real-world power grid network. Empirically, we noted that the game favors the attacker as he benefits more from increased resources than the defender. Further, the minimax defense produces roughly the same expected payoff as an easy-to-compute deterministic load based (DLB) defense when played against a minimax attack strategy. However, DLB performs more poorly than minimax defense when faced with the attacker's best response to DLB. This is likely due to the presence of low-load yet high-payoff nodes, which we also found in our empirical analysis.
KW - Complex networks
KW - Game theory
KW - Power grid defense
UR - http://www.scopus.com/inward/record.url?scp=84911438726&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84911438726&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84911438726
T3 - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
SP - 813
EP - 820
BT - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
T2 - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
Y2 - 5 May 2014 through 9 May 2014
ER -