Multi-Key Privacy-Preserving Training and Classification using Supervised Machine Learning Techniques in Cloud Computing
R. Hari Kishore, Akkapeddi Chandra Sekhar, Pramoda Patro, Debabrata Swain · 2023
Cloud computing contains lots of processing power and storage. Cloud computing and machine learning (ML) techniques enable large-scale data processing. The enhanced ML-based categorization technique is established in the cloud. However, there is a risk of privacy leaking of training data in the data processing. The computational and communication costs of the information possessor(s) must be maintained to a minimum. This study suggests a multi-key enhanced support vector machine (MK-FHE) and multi-key fully homomorphic encryption (MK-FHE) supervised machine learning method for encrypted data (ESVM).The results suggest that MK-FHE protects data privacy and is more effective in processing.