The Ultimate Battle Against Zero-Day Exploits: Toward Fully Autonomous Cyber-Physical Defense

The last decade has shown that networked cyber-physical systems (NCPS) are the future of critical infrastructure such as transportation systems and energy production. However, they have introduced an uncharted territory of security vulnerabilities and a wider attack surface, mainly due to network openness and the deeply integrated physical and cyber spaces. On the other hand, relying on manual analysis of intrusion detection alarms might be effective in stopping run-of-the-mill automated probes but remain useless against the growing number of targeted, persistent, and often AI-enabled attacks on large-scale NCPS. Hence, there is a pressing need for new research directions to provide advanced protection. This paper introduces a novel security paradigm for emerging NCPS, namely Autonomous Cyber-Physical Defense (ACPD). We lay out the theoretical foundations and describe the methods for building autonomous and stealthy cyber-physical defense agents that are able to dynamically hunt, detect, and respond to intelligent and sophisticated adversaries in real time without human intervention. By leveraging the power of game theory and multi-agent reinforcement learning, these self-learning agents will be able to deploy complex cyber-physical deception scenarios on the fly, generate optimal and adaptive security policies without prior knowledge of potential threats, and defend themselves against adversarial learning. Nonetheless, serious challenges including trustworthiness, scalability, and transfer learning are yet to be addressed for these autonomous agents to become the next-generation tools of cyber-physical defense.

I. Introduction

Networked Cyber-Physical Systems (NCPS) and the Inter-net of Things (IoT) have been driving various sectors such as autonomous transportation, remote healthcare, and smart cities. However, they have also expanded the threat surface of connected systems. The risk of an adversary turning off traffic lights, shutting down water treatment plants, or even taking over military infrastructure has never been more real. Indeed, NCPS devices are highly vulnerable to malware attacks, which can be powerful enough to compromise and take full control of devices [1]. Malware can further lead to high-impact attacks such as Distributed Denial of Service (DDoS) launched by large-scale IoT botnets [2]. Moreover, the malware's execution can sabo-tage the NCPS control loop by corrupting the transmitted sensor measurements (e.g., injection attacks) or/and manipulating the control commands sent to the device's actuators (e.g., deception attacks) to severely degrade its performance [3].