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Black-box Stealthy GPS Attacks on Unmanned Aerial Vehicles

Amir Khazraei, Haocheng Meng, Miroslav Pajic

TL;DR

If the closed-loop control system is incrementally exponentially stable, the attacker can cause arbitrarily large deviation in the position trajectory by compromising only the GPS measurements and it is shown that to conduct such stealthy impact-full attack values, the attacker does not need to have access to the model of the system.

Abstract

This work focuses on analyzing the vulnerability of unmanned aerial vehicles (UAVs) to stealthy black-box false data injection attacks on GPS measurements. We assume that the quadcopter is equipped with IMU and GPS sensors, and an arbitrary sensor fusion and controller are used to estimate and regulate the system's states, respectively. We consider the notion of stealthiness in the most general form, where the attack is defined to be stealthy if it cannot be detected by any existing anomaly detector. Then, we show that if the closed-loop control system is incrementally exponentially stable, the attacker can cause arbitrarily large deviation in the position trajectory by compromising only the GPS measurements. We also show that to conduct such stealthy impactfull attack values, the attacker does not need to have access to the model of the system. Finally, we illustrate our results in a UAV case study.

Black-box Stealthy GPS Attacks on Unmanned Aerial Vehicles

TL;DR

If the closed-loop control system is incrementally exponentially stable, the attacker can cause arbitrarily large deviation in the position trajectory by compromising only the GPS measurements and it is shown that to conduct such stealthy impact-full attack values, the attacker does not need to have access to the model of the system.

Abstract

This work focuses on analyzing the vulnerability of unmanned aerial vehicles (UAVs) to stealthy black-box false data injection attacks on GPS measurements. We assume that the quadcopter is equipped with IMU and GPS sensors, and an arbitrary sensor fusion and controller are used to estimate and regulate the system's states, respectively. We consider the notion of stealthiness in the most general form, where the attack is defined to be stealthy if it cannot be detected by any existing anomaly detector. Then, we show that if the closed-loop control system is incrementally exponentially stable, the attacker can cause arbitrarily large deviation in the position trajectory by compromising only the GPS measurements. We also show that to conduct such stealthy impactfull attack values, the attacker does not need to have access to the model of the system. Finally, we illustrate our results in a UAV case study.
Paper Structure (13 sections, 5 theorems, 38 equations, 2 figures)

This paper contains 13 sections, 5 theorems, 38 equations, 2 figures.

Table of Contents

  1. Introduction
  2. Preliminaries
  3. System Model
  4. System and Attack Model
  5. UAV's Dynamical Model
  6. Control Unit
  7. Attack Model
  8. Anomaly Detector
  9. Formalizing Stealthiness and Attack Goals
  10. Formalizing Attack Goal
  11. Vulnerability Analysis of UAV to GPS Attack
  12. Simulation Results
  13. Conclusion

Key Result

Lemma 1

polyanskiy2022information(Monotonicity): Let $P_{X,Y}$ and $Q_{X,Y}$ be two distributions for a pair of variables $X$ and $Y$, and $P_{X}$ and $Q_{X}$ be two distributions for variable $X$. Then,

Figures (2)

  • Figure 1: Control system architecture in the presence of attacks.
  • Figure 2: (a) The $X-Y$ position trajectories of the drone without the attack (blue), with the attack (red) and the output of sensor fusion for $X-Y$ position in the presence of attack. (b,c) The alarm rate for CUSUM and $\chi^2$ ADs for two cases when the system is under attack (attack starts at time t = 0) and when it is attack free over 5000 experiments.

Theorems & Definitions (9)

  • Definition 1
  • Lemma 1
  • Lemma 2
  • Lemma 3
  • Definition 2
  • Lemma 4: khazraei2022attackskhazraei_l4dc22
  • Definition 3
  • Theorem 1
  • proof