Runtime Interchange of Enforcers for Adaptive Attacks: A Security Analysis Framework for Drones

Abstract

Unmanned aerial drones are Cyber-Physical Systems (CPSs) with increasing availability, popularity, and capability. Although other aeronautical and safety-critical industries apply stringent regulations and design approaches, smaller drones tend to have much weaker and informal design requirements. Due to the strong open-source movement in this space, there are numerous opportunities for malicious actors to find weaknesses to attack drone systems, and in parallel develop their own rogue drones. These factors present a risk of damage to people and property in addition to compromise of integrity and availability. However, a formal framework for ethical hacking that combines attacker modelling and launching of attacks is lacking in the literature. To this end, we leverage runtime enforcement, combined with the idea of suspension from synchronous programming to develop the first such formal framework. The proposed framework enables the modelling of complex attack vectors on drones. To facilitate this, we propose a bespoke policy-based runtime enforcement framework called enforcer interchange (EI). It is capable of both individual intent/target-specific attacks as well as more sophisticated combinations of attacks, which it manages by enabling and disabling attack enforcers at runtime in a context-aware manner. To demonstrate our framework, we utilise a quadcopter drone simulator and record the changes in the drone's behaviour as it executes a range of missions under different attacks. Our approach provides a framework for testing drones' resilience and defenses against malicious attacks, as well as exploring the capabilities of rogue drones.