GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption
Year of publication
2024
Authors
Frimpong, Eugene; Nguyen, Khoa; Budzys, Mindaugas; Khan, Tanveer; Michalas, Antonis
Organizations and authors
Publication type
Publication format
Article
Parent publication type
Conference
Article type
Other article
Audience
ScientificPeer-reviewed
Peer-ReviewedMINEDU's publication type classification code
A4 Article in conference proceedingsPublication channel information
Parent publication name
Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing (SAC '24)
Conference
Publisher
Pages
953-962
ISBN
Publication forum
Publication forum level
1
Open access
Open access in the publisher’s service
Yes
Open access of publication channel
Partially open publication channel
License of the publisher’s version
CC BY
Self-archived
Yes
License of the self-archived publication
CC BY
Other information
Fields of science
Computer and information sciences
Internationality of the publisher
International
Language
English
International co-publication
No
Co-publication with a company
No
DOI
10.1145/3605098.3635983
The publication is included in the Ministry of Education and Culture’s Publication data collection
Yes