Common use cases of confidential computing

Mobility
With confidential computing, sensor data from networked vehicles can be aggregated and processed in an end-to-end encrypted and end-to-end verifiable way. It can be mathematically ensured that no relevant conclusions can be drawn from the output data about individual drivers.

Finance
Through confidential computing, a retailer and a credit card company can cross-check their customer and transaction data for potential fraud while neither of them gets access to the original data. The privacy of their customers’ sensitive data is ensured by CC alongside the whole process.

Healthcare
Confidential computing can enable secure multi-party training of AI for different purposes. For example, multiple hospitals can combine their data to train AI for detecting diseases, say, given pictures from CT scans. The patients’ data remains confidential during each step of the process.

Mechanical engineering and manufacturing
Industry 4.0 stands for the approach to increase productivity through massive use of sensors and corresponding data analytics. But companies are often hesitant to share their data or process it in the cloud. Confidential computing can change that.