Distributed aggregative games on graphs in adversarial environments

Bahare Kiumarsi, Tamer Başar

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


Existing solutions to aggregative games assume that all players are fully trustworthy for cooperative tasks or, in a worst-case scenario, are selfish players with no intent to intentionally harm the network. Nevertheless, the need to believe that players will behave consistently exposes the network to vulnerabilities associated with cyber-physical attacks. This paper investigates the effects of cyber-physical attacks on the outcome of distributed aggregative games (DAGs). More specifically, we are seeking to answer two main questions: (1) how a stealthy attack can deviate the game outcome from a cooperative Nash equilibrium, and by doing so, (2) by how much efficiency of a DAG degrades. To this end, we first show that adversaries can stealthily manipulate the outcome of a DAG by compromising the Nash equilibrium solution and consequently lead to an emergent misbehavior or no emergent behavior. This study will intensify the urgency of designing novel resilient solutions to DAGs so that the overall network sustains some notion of acceptable global behavior in the presence of malicious agents. Finally, we corroborate and illustrate our results by providing simulation examples. Simulations reveal that the adverse effect of a compromised agent is considerably worse than that of a selfish agent.

Original languageEnglish (US)
Title of host publicationDecision and Game Theory for Security - 9th International Conference, GameSec 2018, Proceedings
EditorsLinda Bushnell, Radha Poovendran, Tamer Basar
Number of pages18
ISBN (Print)9783030015534
StatePublished - 2018
Event9th International Conference on Decision and Game Theory for Security, GameSec 2018 - Seattle, United States
Duration: Oct 29 2018Oct 31 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11199 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other9th International Conference on Decision and Game Theory for Security, GameSec 2018
Country/TerritoryUnited States


  • Adversarial environment
  • Distributed aggregative games

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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