Inference Privacy
Inference Privacy is a privacy-preserving framework that belongs to the class of edge privacy mechanisms, distinguished by its focus on preventing unauthorized inference of sensitive information from data or model outputs in edge computing environments through obfuscation, perturbation, or access control techniques.
65
Publications
2.2K
Citations
242
Authors
114
Institutions
Publications per year
2017–2026
49
Parents
65
Privacy in Deep Learning: A Survey
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma et al. · arXiv (Cornell University) · 2020 · 98 citations · Full text
Jianneng Cao, Panagiotis Karras, Chedy Raïssi et al. · Proceedings of the VLDB Endowment · 2010 · 88 citations · Full text
Adversarial Privacy-Preserving Graph Embedding Against Inference Attack
Guangchun Luo, Ye Yang, Wei Li et al. · IEEE Internet of Things Journal · 2020 · 84 citations
Towards Privacy-preserving Incentive for Mobile Crowdsensing Under An Untrusted Platform
Zhibo Wang, Jingxin Li, Jiahui Hu et al. · 2019 · 78 citations
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114
Nanyang Technological University
Singapore, Singapore
6 h-index
17 publications
509 citations
University of Southern California
Los Angeles, United States
6 h-index
14 publications
347 citations
California Southern University
Chandler, United States
4 h-index
8 publications
249 citations
Wuhan University
Wuhan, China
4 h-index
12 publications
536 citations

University of Electronic Science and Technology of China
Chengdu, China
3 h-index
10 publications
424 citations
Chalmers University of Technology
Gothenburg, Sweden
3 h-index
3 publications
77 citations

Sun Yat-sen University
Guangzhou, China
3 h-index
8 publications
267 citations
National University of Singapore
Singapore, Singapore
2 h-index
4 publications
403 citations
1–8 of 114
Repository · 7 publications · 216 citations
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5 publications · 297 citations
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2 publications · 111 citations
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1 publications · 21 citations
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PVLDB · 1 publications · 88 citations
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