Phantom Menace: Exploring and Enhancing the Robustness of VLA Models against Physical Sensor Attacks

Vision-Language-Action VLA models revolutionize robotic systems by enabling end-to-end perception-to-action pipelines that integrate multiple sensory modalities, such as visual signals processed by cameras and auditory signals captured by microphones. This multi-modality integration allows VLA...

SoK: How Sensor Attacks Disrupt Autonomous Vehicles: an End-To-End Analysis, Challenges, and Missed Threats

Autonomous vehicles, including self-driving cars, robotic ground vehicles, and drones, rely on complex sensor pipelines to ensure safe and reliable operation. However, these safety-critical systems remain vulnerable to adversarial sensor attacks that can compromise their performance and mission...

HEMA: a Hands-On Exploration Platform for MEMS Sensor Attacks

Automotive safety and security are paramount in the rapidly advancing landscape of vehicular technology. Building safe and secure vehicles demands a profound understanding of automotive systems, particularly in safety and security. Traditional learning approaches, such as reading materials or...

VIMU: Effective Physics-Based Realtime Detection and Recovery against Stealthy Attacks on UAVs

Sensor attacks on robotic vehicles have become pervasive and manipulative. Their latest advancements exploit sensor and detector characteristics to bypass detection. Recent security efforts have leveraged the physics-based model to detect or mitigate sensor attacks. However, these approaches are...