all AI news
RSBA: Robust Statistical Backdoor Attack under Privilege-Constrained Scenarios
March 12, 2024, 4:50 a.m. | Xiaolei Liu, Ming Yi, Kangyi Ding, Bangzhou Xin, Yixiao Xu, Li Yan, Chao Shen
cs.CV updates on arXiv.org arxiv.org
Abstract: Learning-based systems have been demonstrated to be vulnerable to backdoor attacks, wherein malicious users manipulate model performance by injecting backdoors into the target model and activating them with specific triggers. Previous backdoor attack methods primarily focused on two key metrics: attack success rate and stealthiness. However, these methods often necessitate significant privileges over the target model, such as control over the training process, making them challenging to implement in real-world scenarios. Moreover, the robustness of …
abstract arxiv attack methods attacks backdoor cs.ai cs.cr cs.cv however key metrics performance rate robust statistical success systems them type vulnerable
More from arxiv.org / cs.CV updates on arXiv.org
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs
2 days, 3 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Research Scientist
@ Meta | Menlo Park, CA
Principal Data Scientist
@ Mastercard | O'Fallon, Missouri (Main Campus)