Adversarial attacks on voter model dynamics in complex networks

Abstract

This study investigates adversarial attacks conducted to distort voter model dynamics in complex networks. Specifically, a simple adversarial attack method is proposed to hold the state of opinions of an individual closer to the target state in the voter model dynamics. This indicates that even when one opinion is the majority, the vote outcome can be inverted (i.e., the outcome can lean toward the other opinion) by adding extremely small (hard-to-detect) perturbations strategically generated in social networks. Adversarial attacks are relatively more effective in complex (large and dense) networks. These results indicate that opinion dynamics can be unknowingly distorted.

7 pages, 5 figures

References in corpus (6)

• Statistical physics of social dynamics
• Nonequilibrium phase transition in the coevolution of networks and opinions
• Voter Models on Heterogeneous Networks
• Zealots in the mean-field noisy voter model
• Voter models on weighted networks
• Quenched mean-field theory for the majority-vote model on complex networks

Cited by in corpus (3)

• Coexistence of positive and negative information in information-epidemic dynamics on multiplex networks
• Steering cooperation: Adversarial attacks on prisoner's dilemma in complex networks
• Adversarial control of synchronization in complex oscillator networks