A Simulation Platform for Intelligent UAV Cybersecurity and Reliability Analysis

Unmanned aerial vehicles (UAVs) are increasingly adopted in various applications due to their high mobility and advanced sensing capabilities. However, they also face significant security threats and reliability concerns arising from external adversarial attacks and internal system failures. AI and machine learning techniques have shown promise in detecting security threats and anomalies in UAVs, but their effectiveness heavily depends on high-quality UAV security datasets for training. In this paper, we present an open-source simulation platform designed to model diverse UAV security scenarios. Our platform offers flexible customization of attacking effects on major UAV components, including onboard sensors, communication systems, vision modules, and flight control. Additionally, it provides rapid generation and collection of UAV system data under adversarial conditions, facilitating intelligent cybersecurity and reliability analysis. Our experiments successfully simulated over 30 attacking effects toward UAVs, demonstrating our platform's capability to support extensive UAV security research.