Cyber Deception Across Domains: A Comprehensive Survey of Techniques, Challenges, and Perspectives

Abstract

Cloud environments (CE), wireless networks (WN), cyber-physical systems (CPS), industrial control systems (ICS), smart grids (SG), internet of things (IoT), internet of vehicles (IOV), and unmanned aerial vehicles (UAV), are currently popular targets for cyberattacks due to their inherent limitations and vulnerabilities. Each domain has its own attack surfaces, weaknesses, and areas for implementing defense strategies appropriate to its specific conditions. Among the various defense mechanisms discussed in previous years, cyber deception has appeared as a very promising method. This approach allows the defenders to steer the attackers in the wrong direction, get threat intelligence, and at the same time, increase security by engaging with adversaries in deception environments in a proactive manner. Cyber deception has been a topic of investigation in several studies, where specific frameworks and techniques were proposed to identify, delay, or disrupt adversarial behavior. Nevertheless, the contributions of earlier works are frequently limited or missing a unified framework that makes a thorough and comparative study necessary. This survey investigates the cyber deception techniques used in various domains. The first part is about the cores of deception and its background. Next, it presents a summary of the available deception techniques with their modeling by different frameworks like MITRE ATT&CK, D3FEND, and Engage, and intelligent orchestration using reinforcement learning (RL) and game theory (GT). Then, it serves as a thorough systematic review of each selected paper, going over the system design, used deception techniques, evaluation metrics, and limitations on each scheme. The achieved results are compiled into a unified summary table to enable a quick and effective comparison across the domains. It concludes, therefore, by discussing the main challenges, open issues, and areas of research that have not yet been explored, thus making it a valuable source for future research on cyber deception.