Backdoor Removal
Backdoor Removal is a methodological intervention in cybersecurity and machine learning that eliminates covert, unauthorized pathways intentionally embedded in systems or models to enable illicit access or data manipulation.
58
Publications
3.4K
Citations
246
Authors
67
Institutions
Publications per year
2017–2026
55
Parents
58
DeepInspect: A Black-box Trojan Detection and Mitigation Framework for Deep Neural Networks
Huili Chen, Cheng Fu, Jishen Zhao et al. · 2019 · 309 citations · Full text
Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering
Bryant Chen, Wilka Carvalho, Nathalie Baracaldo et al. · arXiv (Cornell University) · 2018 · 231 citations · Full text
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67

Xidian University
Xi'an, China
4 h-index
8 publications
532 citations
University of Illinois Urbana-Champaign
Urbana, United States
3 h-index
3 publications
187 citations

Nanjing University of Aeronautics and Astronautics
Nanjing, China
3 h-index
15 publications
364 citations
Tencent (China)
Shenzhen, China
3 h-index
7 publications
442 citations

Peking University
Beijing, China
3 h-index
4 publications
237 citations

The University of Melbourne
Melbourne, Australia
3 h-index
5 publications
379 citations

Deakin University
Burwood, Australia
3 h-index
3 publications
187 citations

Xi'an Jiaotong University
Xi'an, China
2 h-index
2 publications
73 citations
1–8 of 67
Repository · 18 publications · 1.2K citations
14
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2 publications · 60 citations
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Conference · 1 publications · 241 citations
1
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1 publications · 28 citations
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1 publications · 44 citations
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