Privacy-Preserving Technologies in Data

This cluster of papers focuses on privacy-preserving techniques for data analysis and machine learning, including topics such as differential privacy, federated learning, k-anonymity, secure computation, and location privacy. The papers explore methods to protect sensitive information while performing data mining, machine learning, and statistical analysis.

Journals publishing in this area

1

IEEE Internet of Things Journal

ISSN 2327-46621,718 articles in this topic

246h-index

4.82Impact

17.6KArticles

521.3KCitations

2

IEEE Access

ISSN 2169-35361,591 articles in this topic

358h-index

4.77Impact

106.5KArticles

2.4MCitations

3

Information Sciences

ISSN 0020-0255502 articles in this topic

275h-index

5.05Impact

22.6KArticles

770.6KCitations

4

IEEE Transactions on Industrial Informatics

ISSN 1551-3203280 articles in this topic

252h-index

6.20Impact

9.9KArticles

490.7KCitations

5

IEEE Transactions on Intelligent Transportation Systems

ISSN 1524-9050258 articles in this topic

257h-index

6.14Impact

11.9KArticles

497.9KCitations

6

ACM Computing Surveys

ISSN 0360-0300148 articles in this topic

322h-index

17.05Impact

3.7KArticles

478.9KCitations

7

International Journal of Cloud Computing and Database Management

ISSN 2707-59073 articles in this topic

3h-index

0.23Impact

147Articles

49Citations