Lightweight Detection of Electromagnetic Signal Injection Attacks on Image Sensors

2026-09-07

AI Summary

研究提出了一种利用光学黑像素的轻量级方法来检测针对图像传感器的电磁信号注入攻击，该方法在不同攻击条件下表现出高达99.6%的ROC-AUC值和低至0.027的EER。

Abstract

Electromagnetic signal injection attacks (ESIA) pose a growing threat to image sensors, which are increasingly used in different intelligent systems. By emitting electromagnetic interference, adversaries can manipulate pixel values, potentially misleading downstream artificial intelligence (AI) models and causing unsafe decisions in these systems. We present a lightweight detection method that leverages optically black pixels, which are non-exposed pixels already present in many modern image sensors, to identify the attacks. Our detection approach achieves an area under the receiver operating characteristic curve (ROC-AUC) of up to 99.6\% and an Equal Error Rate (EER) as low as 0.027 across diverse attack conditions. Our method requires minimal computational overhead and no hardware modifications, making it a practical and effective defense for securing vision-based systems against ESIA.

Problem

• Electromagnetic Signal Injection Attacks
• Image Sensors
• Artificial Intelligence
• Unsafe Decisions

Innovation

• Electromagnetic Signal Injection Attacks
• Optically Black Pixels
• Lightweight Detection
• ROC-AUC
• Equal Error Rate