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Luminance-based video backdoor attack against anti-spoofing rebroadcast detection
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Bhalerao, Abhir, Kallas, Kassem, Tondi, Benedetta and Barni, Mauro (2019) Luminance-based video backdoor attack against anti-spoofing rebroadcast detection. In: Multimedia Signal Processing 2019, Kuala Lumpur, Malaysia, 27-29 Sep 2019. Published in: 2019 IEEE 21st International Workshop on Multimedia Signal Processing (MMSP) ISBN 9781728118178. doi:10.1109/MMSP.2019.8901711
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Official URL: https://doi.org/10.1109/MMSP.2019.8901711
Abstract
We introduce a new backdoor attack against a deep-learning video rebroadcast detection network. In addition to the difficulties of working with video signals rather than still images, injecting a backdoor into a deep learning model for rebroadcast detection presents the additional problem that the backdoor must survive the digital-to-analog and analog-to-digital conversion associated to video rebroadcast. To cope with this problem, we have built a backdoor attack that works by varying the average luminance of video frames according to a predesigned sinusoidal function. In this way, robustness against geometric transformation is automatically achieved, together with a good robustness against luminance transformations associated to display and recapture, like Gamma correction and white balance. Our experiments demonstrate the effectiveness of the proposed backdoor attack, especially when the attack is carried out by also corrupting the labels of the attacked training samples.
Item Type: | Conference Item (Paper) | ||||||
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Subjects: | Q Science > QA Mathematics T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
Library of Congress Subject Headings (LCSH): | Neural networks (Computer science), Image processing, Computer security, Biometric identification | ||||||
Journal or Publication Title: | 2019 IEEE 21st International Workshop on Multimedia Signal Processing (MMSP) | ||||||
Publisher: | IEEE Computer Society | ||||||
ISBN: | 9781728118178 | ||||||
Official Date: | 18 November 2019 | ||||||
Dates: |
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DOI: | 10.1109/MMSP.2019.8901711 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Reuse Statement (publisher, data, author rights): | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 28 August 2019 | ||||||
Date of first compliant Open Access: | 28 August 2019 | ||||||
Conference Paper Type: | Paper | ||||||
Title of Event: | Multimedia Signal Processing 2019 | ||||||
Type of Event: | Conference | ||||||
Location of Event: | Kuala Lumpur, Malaysia | ||||||
Date(s) of Event: | 27-29 Sep 2019 | ||||||
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