Revolutionizing Machine Learning Security: The Role of Quantum-Enhanced Federated Learning
E. Kannan, Siddharth Ravikumar, Carmel Mary Belinda M J, K. Vijay, Anstey Vathani, Sriram Kannan · 2024
In today's age of collaborative machine learning where data sharing happens across organizations and privacy becomes a real issue. Old-school methods of securing systems work, but tend to lack against popular new attacks. The research uses a novel approach that uses quantum computing to reimagine what privacy means. An article which deals with the combination of quantum technologies and federated learning systems, specifically discussing how it may set a new standard for data privacy. The plan is to use quantum key distribution and entanglement-based protocols in order to fortify the defences of collaborative machine learning systems against adversarial attacks or unauthorized access, according a consortium statement. The approach to quantum -enhanced federated learning presented provides a solution not only with secure improvements but also implementing more extreme circumstances in decentralised learning scenarios, such as challenges due to different data available and regulatory demands. This paper provides a theoretical benchmark for quantum federated learning and focuses on the underlying concepts leading to excellent security guarantees. Applications and simulations show that this framework can be used in practice with effectiveness. Furthermore, this work benchmarks the scalability of quantum federated learning for different classical and common machine-learning models. The results are a major step towards the goal of making more sophisticated privacy solutions available and allow to create secure, private-first workspace for collaborative machine learning. By leveraging the latest in quantum computing along with specialized tactics designed to combat rapidly evolving data protection threats, this approach will provide a strong foundation for future applications of shared machine learning within distributed quantum environments.