Comparative Analysis of Logistic Regression over Homomorphically Encrypted Data and Decrypted Data

Researcher: Linhle Mbombo, University of Venda
Supervisor: Professor Augustine Munagi and Professor Turgay Çelik, University of the Witwatersrand, Johannesburg

Machine learning (ML) algorithms is improving auto-mated tasks, using data to make predictions and solve clustering problems. The data that is used to fit the model is from institutions, organizations, etc. that have sensitive data. Such as personal, medical and financial data. The research seeks to bridge the security gab and design secure measures of preserving the privacy of data used in the process. Homomorphic encryption concept allows computations on encrypted data. The research uses Paillier algorithm for an encryption scheme.