They see me rollin': inherent vulnerability of the rolling shutter in CMOS image sensors

Conference item

In this paper, we describe how the electronic rolling shutter in CMOS image sensors can be exploited using a bright, modulated light source (e.g., an inexpensive, off-the-shelf laser), to inject fine-grained image disruptions. We demonstrate the attack on seven different CMOS cameras, ranging from cheap IoT to semi-professional surveillance cameras, to highlight the wide applicability of the rolling shutter attack. We model the fundamental factors affecting a rolling shutter attack in an uncontrolled setting. We then perform an exhaustive evaluation of the attack’s effect on the task of object detection, investigating the effect of attack parameters. We validate our model against empirical data collected on two separate cameras, showing that by simply using information from the camera’s datasheet the adversary can accurately predict the injected distortion size and optimize their attack accordingly. We find that an adversary can hide up to 75% of objects perceived by state-of-the-art detectors by selecting appropriate attack parameters. We also investigate the stealthiness of the attack in comparison to a naïve camera blinding attack, showing that common image distortion metrics can not detect the attack presence. Therefore, we present a new, accurate and lightweight enhancement to the backbone network of an object detector to recognize rolling shutter attacks. Overall, our results indicate that rolling shutter attacks can substantially reduce the performance and reliability of vision-based intelligent systems.

Authors: Köhler, S; Lovisotto, G; Birnbach, S; Baker, R; Martinovic, I

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Association for Computing Machinery
• Pages: 399-413
• Publication date: 2021-12-06
• Acceptance date: 2021-09-13
• Event title: Annual Computer Security Applications Conference: ACSAC 2021
• Event location: Virtual event.
• Event website: https://www.acsac.org/
• Event start date: 2021-12-06
• Event end date: 2021-12-10
• DOI: 10.1145/3485832.3488016
• Language: English
• Keywords: FFR