Shaoyuan Xie, Mohamad Habib Fakih, Junchi Lu, Fayzah Alshammari, and Ningfei Wang, University of California, Irvine; Takami Sato, Keio University; Halima Bouzidi, University of California Irvine; Mohammad Abdullah Al Faruque, UC Irvine; Qi Alfred Chen, University of California, Irvine
Autonomous Target Tracking (ATT) systems, especially ATT drones, are widely used in applications such as surveillance, border control, and law enforcement. Thus, the security of ATT is highly critical for real-world applications. Under the scope, we present a new type of attack: distance-pulling attacks (DPA), which exploits vulnerabilities in ATT systems to dangerously reduce tracking distances, leading to drone capturing, increased susceptibility to sensor attacks, or even physical collisions. We present FlyTrap, a novel physical-world attack framework that employs an adversarial umbrella as a deployable and domain-specific attack vector to achieve these goals. This demonstration will include videos and figures of the generated FlyTrap adversarial umbrellas and the end-to-end consequences.
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