Let’s stride blindfolded in a forest : sublinear multi-client decision trees evaluation
Decision trees are popular machine-learning classification models due to their simplicity and effectiveness. Tai et al. (ESORICS ’17) propose a privacy-preserving decision-tree evaluation protocol purely based on additive homomorphic encryption, without introducing dummy nodes for hiding the tree s...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/148326 |