Neutralization of IMU-Based GPS Spoofing Detection using external IMU sensor and feedback methodology

TL;DR

This paper presents a novel attack model that neutralizes IMU-based GPS spoofing detection in autonomous vehicles by using an external IMU sensor and feedback methodology, demonstrating undetectable spoofing in experiments.

Contribution

It introduces an attack approach that bypasses existing IMU-based GPS spoofing detection methods using external sensors and sensor fusion techniques.

Findings

Attack values can be injected without detection.

External IMU sensors can steal internal dynamic state information.

Proposed method reduces anomaly detection in GPS spoofing attacks.

Abstract

Autonomous Vehicles (AVs) refer to systems capable of perceiving their states and moving without human intervention. Among the factors required for autonomous decision-making in mobility, positional awareness of the vehicle itself is the most critical. Accordingly, extensive research has been conducted on defense mechanisms against GPS spoofing attacks, which threaten AVs by disrupting position recognition. Among these, detection methods based on internal IMU sensors are regarded as some of the most effective. In this paper, we propose a spoofing attack system designed to neutralize IMU sensor-based detection. First, we present an attack modeling approach for bypassing such detection. Then, based on EKF sensor fusion, we experimentally analyze both the impact of GPS spoofing values on the internal target system and how our proposed methodology reduces anomaly detection within the target system. To this end, this paper proposes an attack model that performs GPS spoofing by stealing internal dynamic state information using an external IMU sensor, and the experimental results demonstrate that attack values can be injected without being detected.