ML with HE: Privacy Preserving Machine Learning Inferences for Genome Studies
Published in ACM CCS 2021 PPML Workshop, 2021
Proposes a homomorphic encryption framework for secure tumor classification (SVM + XGBoost) on encrypted genomic data.
Recommended citation: Mağara, Ş. S., Yıldırım, C., Yaman, F., Dilekoğlu, B., Tutaş, F. R., Öztürk, E., Kaya, K., Taştan, Ö., & Savaş, E. (2021). ML with HE: Privacy Preserving Machine Learning Inferences for Genome Studies. arXiv preprint, arXiv:2110.11446. https://doi.org/10.48550/arXiv.2110.11446
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