Quantifying the Engagement Effectiveness of Cyber Cognitive Attacks: A Behavioral Metric for Disinformation Campaigns

2025-10-17

AI Summary

As misinformation-driven cognitive attacks grow increasingly sophisticated, existing methods struggle to quantitatively assess user engagement efficacy and the intensity of cognitive impact. Method: This paper proposes a weighted interaction metric framework that introduces, for the first time, a behavioral depth weighting mechanism—integrating interaction type, frequency, scale, and response ratio to attacker-generated content—to enable multidimensional evaluation of cognitive attack participation on social platforms. The approach combines behavioral analysis, weighted indicator modeling, and real-world social media data mining. Contribution/Results: Validated across multiple misinformation case studies, the framework not only differentiates propagation breadth but also precisely identifies high-impact cognitive attack nodes. It significantly enhances the interpretability and operationality of malicious network influence assessment, offering a novel paradigm and practical toolset for cognitive-domain defense strategies.

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Application Domains: Misinformation & Fake News
• Multiagent Systems: Adversarial Agents

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Web Mining and Content Analysis: Content-based information diffusion
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

As disinformation-driven cognitive attacks become increasingly sophisticated, the ability to quantify their impact is essential for advancing cybersecurity defense strategies. This paper presents a novel framework for measuring the engagement effectiveness of cognitive attacks by introducing a weighted interaction metric that accounts for both the type and volume of user engagement relative to the number of attacker-generated transmissions. Applying this model to real-world disinformation campaigns across social media platforms, we demonstrate how the metric captures not just reach but the behavioral depth of user engagement. Our findings provide new insights into the behavioral dynamics of cognitive warfare and offer actionable tools for researchers and practitioners seeking to assess and counter the spread of malicious influence online.

Problem

• Quantifying engagement effectiveness of cognitive cyber attacks
• Measuring behavioral depth in disinformation campaign interactions
• Developing metrics to counter malicious online influence spread

Innovation

• Weighted interaction metric measures engagement effectiveness
• Framework accounts for user engagement type and volume
• Model captures behavioral depth in disinformation campaigns