They see me rollin': inherent vulnerability of the rolling shutter in CMOS image sensors
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 c...
| Main Authors: | , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Association for Computing Machinery
2021
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| _version_ | 1797075994508525568 |
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| author | Köhler, S Lovisotto, G Birnbach, S Baker, R Martinovic, I |
| author_facet | Köhler, S Lovisotto, G Birnbach, S Baker, R Martinovic, I |
| author_sort | Köhler, S |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-06T23:57:57Z |
| format | Conference item |
| id | oxford-uuid:74e44ce9-78e7-4d60-bc28-c7251addbd4c |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T23:57:57Z |
| publishDate | 2021 |
| publisher | Association for Computing Machinery |
| record_format | dspace |
| spelling | oxford-uuid:74e44ce9-78e7-4d60-bc28-c7251addbd4c2022-03-26T20:05:58ZThey see me rollin': inherent vulnerability of the rolling shutter in CMOS image sensorsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:74e44ce9-78e7-4d60-bc28-c7251addbd4cEnglishSymplectic ElementsAssociation for Computing Machinery2021Köhler, SLovisotto, GBirnbach, SBaker, RMartinovic, IIn 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. |
| spellingShingle | Köhler, S Lovisotto, G Birnbach, S Baker, R Martinovic, I They see me rollin': inherent vulnerability of the rolling shutter in CMOS image sensors |
| title | They see me rollin': inherent vulnerability of the rolling shutter in CMOS image sensors |
| title_full | They see me rollin': inherent vulnerability of the rolling shutter in CMOS image sensors |
| title_fullStr | They see me rollin': inherent vulnerability of the rolling shutter in CMOS image sensors |
| title_full_unstemmed | They see me rollin': inherent vulnerability of the rolling shutter in CMOS image sensors |
| title_short | They see me rollin': inherent vulnerability of the rolling shutter in CMOS image sensors |
| title_sort | they see me rollin inherent vulnerability of the rolling shutter in cmos image sensors |
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