Zobrazeno 1 - 3
of 3
pro vyhledávání: '"local ϵ-differential privacy"'
Publikováno v:
IEEE Access, Vol 12, Pp 139692-139710 (2024)
With the increasing importance of data privacy protection, various privacy-preserving machine learning methods have been proposed. In the clustering domain, various algorithms with a federated learning framework (i.e., federated clustering) have been
Externí odkaz:
https://doaj.org/article/fbfa15c0d902444ab5a134f9c0c55b93
Privacy-preserving Data Aggregation against Malicious Data Mining Attack for IoT-enabled Smart Grid.
Publikováno v:
ACM Transactions on Sensor Networks; Aug2021, Vol. 17 Issue 3, p1-25, 25p
Autor:
Vicenç Torra
Data privacy technologies are essential for implementing information systems with privacy by design.Privacy technologies clearly are needed for ensuring that data does not lead to disclosure, but also that statistics or even data-driven machine learn
