Paralyzing Drones via EMI Signal Injection on Sensory Communication Channels

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Abstract

An inertial measurement unit (IMU) takes the key responsibility for the attitude control of drones. It comprises various sensors and transfers sensor data to the drone’s control unit. If it reports incorrect data, the drones cannot maintain their attitude and will consequently crash down to the ground. Therefore, several anti-drone studies have focused on causing the significant fluctuations in the IMU sensor data by resonating the mechanical structure of the internal sensors using a crafted acoustic wave. However, this approach is limited in terms of efficacy for several reasons. As the structural details of each sensor in an IMU significantly differ by type, model, and manufacturer, the attack needs to be conducted independently for each sensor. Furthermore, it can be easily mitigated by using other supplementary sensors that are not corrupted by the attack or inexpensive plastic shielding. In this paper, we propose a novel anti-drone technique that effectively corrupts any IMU sensor data regardless of the sensor’s type, model, and manufacturer. Our key idea is to distort the communication channel between the IMU and control unit of the drone by using an electromagnetic interference (EMI) signal injection. Experimentally, for a given control unit board, regardless of the sensor used, we discovered a distinct susceptible frequency at which an EMI signal greatly distorted the sensor data. Compared to a general EM pulse (EMP) attack, our work requires considerably less power since it targets the specific susceptible frequency. It can also reduce collateral damage from the EMP attack (e.g., permanent damage to the electric circuits of any nearby devices). For practical evaluations, we demonstrated the feasibility of the attack using real drones, wherein it instantly paralyzed the drones. Lastly, we conclude by presenting practical challenges for its mitigation.

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APA

Jang, J., Cho, M., Kim, J., Kim, D., & Kim, Y. (2023). Paralyzing Drones via EMI Signal Injection on Sensory Communication Channels. In 30th Annual Network and Distributed System Security Symposium, NDSS 2023. The Internet Society. https://doi.org/10.14722/ndss.2023.24616

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