DPM: Towards Accurate Drone Position Manipulation

While existing methods can disrupt drone invasions in a protected airspace, none of them is able to accurately guide a drone to a desired location for safe handling. To address this issue, the
Drone Position Manipulation (DPM)
attack is proposed in this article to explore weaknesses in common navigation algorithms of consumer drones. The main advantage of DPM is that it can accurately redirect an invading drone to a desired location, by carefully crafting the spoofed guidance inputs of the drone to exploit the adjustment of path-following navigation algorithms. Compared with existing methods, this is the first work to achieve such accurate quantitative control. Another main contribution of this work is that it explores three fundamental components (i.e., guidance sensing, state estimation, and navigation control) together to enable the quantitative manipulation of flight paths, different from all existing methods. Furthermore, a formal analysis of the attack range is presented for investigating where a drone can be redirected from its target under given constraints. The evaluation on the Software-in-the-loop (SITL) module of
ArduPilot
system shows that the proposed attack is able to not only accurately lead a drone to a redirected destination but also make it fairly far away from its target. Lastly, the proposed attack can be applied to many autopiloted systems, because it exploits common weaknesses in these systems.