Confidential computing use cases

Confidential computing offers a broad range of applications, primarily falling into two categories:

1. Enhancing the security of existing applications: By running applications within CCEs, you can ensure security against infrastructure-layer attacks, including compromised host operating systems, malicious administrators, and physical threats. These applications are protected from data breaches and have added compliance benefits. The latter are extremely relevant when talking about SaaS platforms in regulated industries were customer data is at risk.
2. Developing new privacy-preserving applications: by leveraging confidential computing, a lot of new applications for secure data sharing are now possible. Just as an example, we can think of competitor companies aiming to identify trends or information about customers without divulging confidential information. They could build a an app to intersect the two given customer databases and run it into a CCE, send the CCE a certificate to verify the integrity of the . This approach extends to various applications, like joint AI model training, benchmarking, census data analysis, and secure multi-party computations. An exemplary privacy-preserving app, Signal Messenger, employs Intel SGX for secure contact discovery, providing unmatched security against employee or hacker access. These assurances give Signal a distinct competitive advantage over competitors such as WhatsApp.

In the following, we will dive deeper into more specific use cases of confidential computing.