AI-Enhanced Deception Technologies for Cyber Defense: A Cognitive Load Framework for Professional Attack Surface Management

Abstract

A cognitive load paradigm for professional management of attack surfaces and the employment of AI-enabled deception technologies in cyber defense are the topics of this paper's inquiry. The study's primary objective is to shed light on the challenges faced by cybersecurity professionals in the face of evolving cyber threats. To do this, we test how AI and deception strategies work together to reduce cognitive burden and improve decision-making during defense operations. The methodology includes analyzing current AI-based deceit models, using case studies and real-life instances, and developing new ones. Important findings include the fact that security responders are not overburdened and that deception methods backed by AI, such as decoy systems and dynamic honeypots, can successfully divert the attention of attackers.