TY - GEN
T1 - On Poisoned Wardrop Equilibrium in Congestion Games
AU - Pan, Yunian
AU - Zhu, Quanyan
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - Recent years have witnessed a growing number of attack vectors against increasingly interconnected traffic networks. Informational attacks have emerged as the prominent ones that aim to poison traffic data, misguide users, and manipulate traffic patterns. To study the impact of this class of attacks, we propose a game-theoretic framework where the attacker, as a Stackelberg leader, falsifies the traffic conditions to change the traffic pattern predicted by the Wardrop traffic equilibrium, achieved by the users, or the followers. The intended shift of the Wardrop equilibrium is a consequence of strategic informational poisoning. Leveraging game-theoretic and sensitivity analysis, we quantify the system-level impact of the attack by characterizing the concept of poisoned Price of Anarchy, which compares the poisoned Wardrop equilibrium and its non-poisoned system optimal counterpart. We use an evacuation case study to show that the Stackelberg equilibrium can be found through a two-time scale zeroth-order learning process and demonstrate the disruptive effects of informational poisoning, indicating a compelling need for defense policies to mitigate such security threats.
AB - Recent years have witnessed a growing number of attack vectors against increasingly interconnected traffic networks. Informational attacks have emerged as the prominent ones that aim to poison traffic data, misguide users, and manipulate traffic patterns. To study the impact of this class of attacks, we propose a game-theoretic framework where the attacker, as a Stackelberg leader, falsifies the traffic conditions to change the traffic pattern predicted by the Wardrop traffic equilibrium, achieved by the users, or the followers. The intended shift of the Wardrop equilibrium is a consequence of strategic informational poisoning. Leveraging game-theoretic and sensitivity analysis, we quantify the system-level impact of the attack by characterizing the concept of poisoned Price of Anarchy, which compares the poisoned Wardrop equilibrium and its non-poisoned system optimal counterpart. We use an evacuation case study to show that the Stackelberg equilibrium can be found through a two-time scale zeroth-order learning process and demonstrate the disruptive effects of informational poisoning, indicating a compelling need for defense policies to mitigate such security threats.
KW - Adversarial attack
KW - Congestion games
KW - Sensitivity analysis
KW - Stackelberg game
UR - http://www.scopus.com/inward/record.url?scp=85151155151&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85151155151&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-26369-9_10
DO - 10.1007/978-3-031-26369-9_10
M3 - Conference contribution
AN - SCOPUS:85151155151
SN - 9783031263682
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 191
EP - 211
BT - Decision and Game Theory for Security - 13th International Conference, GameSec 2022, Proceedings
A2 - Fang, Fei
A2 - Xu, Haifeng
A2 - Hayel, Yezekael
PB - Springer Science and Business Media Deutschland GmbH
T2 - 13th International Conference on Decision and Game Theory for Security, GameSec 2022
Y2 - 26 October 2022 through 28 October 2022
ER -