Abstract
As asynchronous event data is more frequently engaged in various vision tasks, the risk of backdoor attacks becomes more evident. However, research into the potential risk associated with backdoor attacks in asynchronous event data has been scarce, leaving related tasks vulnerable to potential threats. This paper has uncovered the possibility of directly poisoning event data streams by proposing Event Trojan framework, including two kinds of triggers, i.e., immutable and mutable triggers. Specifically, our two types of event triggers are based on a sequence of simulated event spikes, which can be easily incorporated into any event stream to initiate backdoor attacks. Additionally, for the mutable trigger, we design an adaptive learning mechanism to maximize its aggressiveness. To improve the stealthiness, we introduce a novel loss function that constrains the generated contents of mutable triggers, minimizing the difference between triggers and original events while maintaining effectiveness. Extensive experiments on public event datasets show the effectiveness of the proposed backdoor triggers. We hope that this paper can draw greater attention to the potential threats posed by backdoor attacks on event-based tasks.
Original language | English |
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Title of host publication | Computer Vision – ECCV 2024 |
Subtitle of host publication | 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part VII |
Editors | Aleš Leonardis, Elisa Ricci, Stefan Roth, Olga Russakovsky, Torsten Sattler, Gül Varol |
Publisher | Springer Cham |
Pages | 315–332 |
Number of pages | 18 |
Edition | 1st |
ISBN (Electronic) | 9783031726675 |
ISBN (Print) | 9783031726668 |
DOIs | |
Publication status | Published - 28 Sept 2024 |
Event | 18th European Conference on Computer Vision, ECCV 2024 - Milan, Italy Duration: 29 Sept 2024 → 4 Oct 2024 https://eccv.ecva.net/Conferences/2024 https://link.springer.com/book/10.1007/978-3-031-73232-4 |
Publication series
Name | Lecture Notes in Computer Science |
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Volume | 15065 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Name | ECCV: European Conference on Computer Vision |
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Conference
Conference | 18th European Conference on Computer Vision, ECCV 2024 |
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Country/Territory | Italy |
City | Milan |
Period | 29/09/24 → 4/10/24 |
Internet address |