The future of data privacy: Confidential Computing explained

 

Confidential Computing is redefining how sensitive data is handled in the cloud. This paper explains how it protects data while it’s in use, enabling secure collaboration between institutions without compromising confidentiality.

Readers will learn how secure enclaves and Multi-Party Computation work together to create a verifiable privacy layer that meets DORA and GDPR requirements. The PDF includes real-world examples showing how financial institutions and regulators are deploying these methods to achieve compliance and operational resilience.

Download the paper to understand why Confidential Computing is fast becoming the cornerstone of privacy-first data strategies.

 

What if you could use sensitive data without ever seeing it? Here’s how Confidential Computing makes it real.

A practical explainer for non-technical stakeholders and decision-makers. This eBook demystifies Confidential Computing, focusing on how technologies like MPC allow encrypted data to be used without ever being exposed. Includes benefits, use cases, and how to get started securely.

 

Why traditional approaches aren’t enough

Most organizations are sitting on valuable data, but they can’t use it the way they want to. Legal restrictions, privacy concerns, and trust barriers create silos, both inside companies and between them. This leads to missed opportunities, duplicated efforts, and slower innovation. 

What is Confidential Computing?

By securing data in use, Confidential Computing closes the last major gap in the data protection lifecycle complementing encryption at rest and in transit.

This makes it possible to unlock insights, fuel innovation, and enable secure collaboration across organizational and jurisdictional boundaries.

What problems does it solve?

● Joint analytics across organizations:  Run shared computations without giving up your data

● Privacy-sensitive AI training:  Combine datasets to train better models without leaking information.

And more.

Real-world use cases:

● Healthcare 
● Banking and insurance 
● Automotive industry
● Public sectors