Hierarchical Clustering via Single and Complete Linkage Using Fully Homomorphic Encryption. [PDF]
Sensors (Basel)Sokhonn L, Park YS, Lee MK.
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Predicting Genetic Disorder on Encrypted Data with Concrete ML Homomorphic Encryption Library
This paper investigates the use of Fully Homomorphic Encryption (FHE) through the ConcreteML library to ensure data privacy in machine learning applications. The research focuses on predicting genetic disorders using a Gradient Boosted Tree model trained
Nguyen, Ngoc Hai Dang
core
Privacy protection of communication networks using fully homomorphic encryption based on network slicing and attributes. [PDF]
Sci RepWang W, Liu R, Cheng S.
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Privacy-preserving biological age prediction over federated human methylation data using fully homomorphic encryption. [PDF]
Genome ResGoldenberg M +4 more
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Summation-based Private Segmented Membership Test from Threshold-Fully Homomorphic Encryption. [PDF]
Proc Priv Enhanc TechnolKoirala N +3 more
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Lightweight Privacy-Preserving Blockchain Framework for Healthcare: A Simulation-Based Approach to Reducing Computational Overhead. [PDF]
Blockchain Healthc TodayAhmed MA +3 more
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A Regev-type fully homomorphic encryption scheme using modulus switching. [PDF]
ScientificWorldJournal, 2014 Chen Z, Wang J, Chen L, Song X.
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Safeguarding biomedical AI: a critical scoping review of privacy-enhancing technologies, hybrid approaches, and deployment models. [PDF]
Front Digit HealthAy S, Topaloglu U, Zhang W.
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privateST: a feasible framework for privacy-preserving spatial transcriptomics prediction from histopathology images. [PDF]
Sci RepKim H, Kim M, Han B.
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Privacy-Preserving and Poisoning-Robust Federated Learning for Industrial IoT. [PDF]
Sensors (Basel)Yin H, Chen C, Zhang J, Yu D, Liu S.
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