MIT researchers have developed a quantum-based security protocol to protect sensitive data during cloud-based deep-learning computations. By encoding data into light, this technique prevents attackers from intercepting or copying it, thanks to quantum mechanics principles. This innovation is particularly valuable in sectors like healthcare, where data privacy is crucial.
The protocol allows hospitals and financial organisations to utilise cloud-based AI models for tasks such as medical diagnoses or financial forecasting without risking patient or customer privacy. It uses the “no-cloning” principle of quantum physics, ensuring that data remains secure while maintaining a model’s high accuracy—up to 96% in initial tests.
This security method represents a significant step forward in secure cloud computing, enabling two-way protection: client data remains hidden from the server, and the server’s proprietary model is shielded from the client. The MIT team plans to explore broader applications, such as federated learning and quantum operations, which could further enhance data security and AI model accuracy in collaborative computing scenarios. Source