A Survey on Privacy-Preserving Machine Learning Inference
This paper examines methods to secure machine learning inference (ML inference) so that sensitive data remains private and proprietary models are protected during remote processing. We review several approaches—from cryptographic techniques like homomorphic encryption (HE) and secure multi-party co...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Gdańsk University of Technology
2025-07-01
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| Series: | TASK Quarterly |
| Subjects: | |
| Online Access: | https://journal.mostwiedzy.pl/TASKQuarterly/article/view/3534 |
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