Design and implementation of a privacy-preserving data mining framework

Thesis Abstract

The project aims to develop a privacy-preserving data mining framework that allows organizations to extract valuable insights from sensitive data without compromising individual privacy. The framework will utilize advanced cryptographic techniques and secure multi-party computation protocols to enable collaborative data analysis while ensuring that the raw data remains encrypted and private. The project will address the growing need for privacy-preserving data mining solutions in various domains, including healthcare, finance, and social media.