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Tag: Privacy-Preserving Machine Learning

Wildest Dreams: Reproducible Research in Privacy-Preserving Neural Network Training

Paper Accepted at PETS 2024

7.3.2024
  • News
  • Research
GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption

Paper Accepted at ACM SAC 2024

31.1.2024
  • News
Blind Faith: Privacy-Preserving Machine Learning using Function Approximation

Paper Accepted at TrustCom 2023

19.9.2023
  • News
A More Secure Split: Enhancing the Security of Privacy-Preserving Split Learning

Paper Accepted at NordSec 2023

19.9.2023
  • News
Forward and Backward Propagation

Paper Accepted at SecureComm 2023

31.8.2023
  • News
U-shaped Split-Learning

Paper Accepted at PST 2023

4.7.2023
  • News

Best Students Paper Award at ISCC'21

16.9.2021
  • News
Blind Faith: Privacy-Preserving Machine Learning using Function Approximation

Paper accepted at ISCC 2021

2.8.2021
  • News

Contact persons

Antonis Michalas
Marko Helenius

NISEC

Network and Information Security Group

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