Towards Proactive Defense Against Cyber Cognitive Attacks
Bonnie Rushing, Mac-Rufus Umeokolo, Shouhuai Xu
TL;DR
The paper tackles the problem of cyber cognitive attacks that leverage disruptive innovations (DIs) to manipulate decision-making, highlighting the lack of predictive tools to forecast future DIs. It proposes a two-model predictive framework: Model 1 uses linear regression to forecast when new DIs will emerge, and Model 2 uses qualitative DI attributes to predict their capabilities, guiding proactive defenses. Through a case study of 11 historical DIs (1971–2017), it demonstrates feasibility, maps DIs to DISARM and MITRE ATT&CK TTPs, and provides defense strategies including a 2021 humanoid robot prediction and corresponding countermeasures. The framework aims to enable cross-disciplinary, proactive defense planning by predicting both timing and attributes of emerging DIs and aligning them with established defensive frameworks, thereby informing policy, awareness, and resource allocation.
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.