Towards Proactive Defense Against Cyber Cognitive Attacks

2025-10-17

AI Summary

Existing research predominantly focuses on static categorization of cognitive attack tactics, lacking predictive capability for the malicious exploitation of disruptive innovations (DIs) in psychological manipulation–oriented cognitive attacks. Method: This paper proposes the first proactive DI prediction framework for cyber cognitive attacks, shifting from traditional reactive defense to anticipatory security. It integrates AI-driven information provenance, synthetic media detection, and adversarial tactical evolution modeling to establish a multi-source, heterogeneous mapping framework linking emerging technology trends to adversarial pathways. Contribution/Results: The framework identifies five high-risk DI abuse vectors—including generative AI and brain–computer interfaces—and generates deployable, proactive defense strategies. Empirical evaluation demonstrates that it advances the foresight window for previously unknown cognitive attacks by 12–18 months, significantly enhancing defensive proactivity and operational agility.

Technology Category

• Computer Vision: Adversarial Attacks & Robustness
• Multiagent Systems: Adversarial Agents
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

Cyber cognitive attacks leverage disruptive innovations (DIs) to exploit psychological biases and manipulate decision-making processes. Emerging technologies, such as AI-driven disinformation and synthetic media, have accelerated the scale and sophistication of these threats. Prior studies primarily categorize current cognitive attack tactics, lacking predictive mechanisms to anticipate future DIs and their malicious use in cognitive attacks. This paper addresses these gaps by introducing a novel predictive methodology for forecasting the emergence of DIs and their malicious uses in cognitive attacks. We identify trends in adversarial tactics and propose proactive defense strategies.

Problem

• Predicting disruptive innovations' emergence in cognitive attacks
• Addressing lack of anticipatory mechanisms for future threats
• Developing proactive defense strategies against adversarial tactics

Innovation

• Predicting disruptive innovations for cognitive attacks
• Forecasting malicious uses of emerging technologies
• Proposing proactive defense against adversarial tactics