Noise Addition
Noise Addition is a data perturbation technique within the class of data anonymization methods that introduces random or pseudo-random variations into a dataset to obscure individual data points, thereby preventing re-identification while preserving overall statistical properties.
234
Publications
10.3K
Citations
726
Authors
380
Institutions
Publications per year
2017–2026
77
234
Kristen LeFevre, David J. DeWitt, Raghu Ramakrishnan · 2005 · 1.1K citations
Assessing robustness of radiomic features by image perturbation
Scientific Reports · 2019 · 243 citations · Full text
Jaehun Kim, Stjepan Picek, Annelie Heuser et al. · IACR Transactions on Cryptographic Hardware and Embedded Systems · 2019 · 219 citations · Full text
Ji Wang, Jianguo Zhang, Weidong Bao et al. · 2018 · 196 citations · Full text
1–5 of 234
726
6
h-index
6
h-index
5
h-index
4
h-index
4
h-index
1–5 of 726
380

Universitat Rovira i Virgili
Tarragona, Spain
7 h-index
13 publications
423 citations

University of Electronic Science and Technology of China
Chengdu, China
6 h-index
17 publications
896 citations
University of Newcastle Australia
Newcastle, Australia
4 h-index
6 publications
210 citations
Beijing Jiaotong University
Beijing, China
4 h-index
9 publications
391 citations
Nanyang Technological University
Singapore, Singapore
4 h-index
12 publications
1.7K citations
Queen's University Belfast
Belfast, United Kingdom
3 h-index
10 publications
295 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
7 publications
429 citations
Ningbo University
Ningbo, China
3 h-index
8 publications
150 citations
1–8 of 380
9 publications · 493 citations
9
h-index
Repository · 9 publications · 370 citations
8
h-index
3 publications · 115 citations
3
h-index
3 publications · 87 citations
3
h-index
JPC · 3 publications · 96 citations
3
h-index
1–5