semantic_scholarProceedings on Privacy Enhancing Technologies
FHEON: A Configurable Framework for Developing Privacy-Preserving Encrypted Neural Networks
Nges Brian Njungle, Eric Jahns, Michel A. Kinsy
TL;DR: FHEON is presented, an open-source configurable framework for developing privacy-preserving neural network models for inference using the CKKS scheme of HE, and outperform all state-of-the-art HE inference works in both latency and memory utilization.
The widespread adoption of Machine Learning as a Service raises critical privacy and security concerns, particularly about data confidentiality and trust in both cloud providers and the machine learning models provided. Homomorphic Encryption (HE) has emerged as a promising solut…