Securing AI with AI: Novel Framework for Drone Communication Security
摘要
Autonomous drone swarms operating in potentially hostile environments and communicating over inherently insecure wireless channels require robust security architectures. While AI-based algorithms are effective in detecting communication anomalies and intrusions, their deployment in low-power environments like drones is challenging, and the integrity of AI-driven decisions can also be compromised. This paper discusses a comprehensive drone communication framework that enhances security by leveraging an efficient PMU design for minimally intrusive, real-time system tracing. Our approach improves system resilience by combining PMU data to (i) secure the integrity of AI-based decisions and (ii) detect intrusions through network profiling. The framework integrates the hardware Root-of-Trust of the target System-on-Chip to ensure integrity and privacy.