Traffic networks are vulnerable to disinformation attacks.

Area of Science:

• Computer Science
• Urban Planning
• Sociology

Background:

• Disinformation poses a growing societal threat, with critical infrastructure vulnerabilities often overlooked.
• Urban traffic networks are susceptible to disinformation-based attacks manipulating driver decisions.
• Such attacks can create large-scale traffic congestion, impacting city functionality.

Purpose of the Study:

• To analyze the impact of disinformation campaigns on urban traffic networks.
• To investigate the optimization problem for adversaries seeking to maximize traffic disruption.
• To compare the effectiveness of different targeting strategies for disinformation attacks.

Main Methods:

• Modeling disinformation attacks on urban traffic networks.
• Analyzing two scenarios: drivers persuaded towards or away from a location.
• Proving the computational intractability of finding an optimal attack strategy.
• Evaluating a suboptimal heuristic for adversary targeting.

Main Results:

• Optimal disinformation attack strategies are computationally intractable.
• A heuristic approach is necessary for adversaries.
• Concentrating attack targets in a business district causes more widespread disruption than spreading them across the city.
• Disruption can extend up to 2 km from targeted areas.

Conclusions:

• Urban traffic networks exhibit vulnerabilities to behavioral manipulation via disinformation.
• Critical infrastructure security must consider psychological and social engineering threats, not just technical ones.
• Targeted disinformation campaigns can have significant and far-reaching impacts on public infrastructure.