Electromagnetic Signal Injection Attack

Electromagnetic signal injection attacks (ESIAs) exploit vulnerabilities in electronic systems to manipulate sensor data, primarily targeting cameras and LiDARs used in autonomous systems and other critical infrastructure. Current research focuses on understanding the mechanisms of these attacks, including analyzing their impact on image and point cloud data processing, and developing both signal-specific and universal attack methods, often leveraging adversarial examples and machine learning techniques. This research is crucial for improving the security and reliability of AI-powered systems, as ESIAs can lead to misinterpretations of sensor data with potentially catastrophic consequences in applications like autonomous driving and security surveillance.