Written byMark Russinovich, Chief Technology Officer and Technical Fellow, Microsoft Azure
The exponential growth of datasets has resulted in growing scrutiny of how data is exposed—both from a consumer data privacy and compliance perspective. In this context,confidential computingbecomes an important tool to help organizations meet their privacy and security needs surrounding business and consumer data.
Confidential computing technology encrypts data in memory and only processes it once the cloud environment is verified, preventing data access from cloud operators, malicious admins, and privileged software such as the hypervisor. It helps keep data protected throughout its lifecycle—in addition to existing solutions of protecting data at rest and in transit, data is now protected while in use.
Thanks to confidential computing, organizations across the world can now unlock opportunities that were not possible before. For example, they can now benefit from multi-party data analytics and machine learning that combine datasets from parties that would have been unwilling or unable to share them, keeping data private across participants. In fact,RBC created a platformfor privacy-preserving analytics for customers to opt-in for more optimized discounts. The platform generates insights into consumer purchasing preferences by confidentially combining RBC’s credit and debit card transactions with retailer data of what specific items consumers purchased.