This research leverages epidemiological principles to create more effective rumor detection systems for social media by modeling how false information spreads like contagious diseases.

• Introduces EPIGrumor framework that adapts infection dynamics to analyze rumor propagation patterns
• Captures the varying susceptibility of different users to misinformation
• Achieves superior performance by considering both content and propagation characteristics
• Demonstrates resilience against adversarial attacks compared to traditional approaches

This advancement is critical for security professionals as it provides more robust tools to combat misinformation campaigns that threaten public trust and information integrity in digital spaces.

Epidemiology-informed Network for Robust Rumor Detection