What is Confidential Computing?


Confidential computing; focuses on software and hardware-based security. Confidential computing ensures that data is secured and encrypted against risks such as malicious individuals, network vulnerabilities, or any threat to hardware or software-based technologies that can be compromised. Confidential computing can be defined as a cloud computing system that isolates sensitive data in a protected CPU enclave while processing information. Transactions made within the scope of confidential information processing can be accessed with the authorized programming code.

Confidential information processing is not visible to anything or anyone, including the cloud provider. As business leaders increasingly rely on public and hybrid cloud services, data privacy is legally required in the cloud. The primary goal of confidential computing is to provide leaders with greater assurance that their data in the cloud is protected and confidential. Within the scope of confidential information processing; data must be unencrypted in memory before data is processed.*

Why Should You Use Confidental Computing?

It is very important that you use confidential computing to protect sensitive data. When used with private key control and data encryption at rest and in transit; confidential computing creates huge financial savings for an inflexible, expensive company handling sensitive or highly regulated datasets and application workloads.

To protect intellectual property: Confidential computing isn't just for data protection. It is also essential for protecting proprietary business logic, analytical functions, machine learning algorithms or any application.

Ability to securely share with partners on new cloud solutions: The company team can securely share sensitive data with other teams on another company's proprietary platforms to create new solutions.

To protect end-to-end processed data: End-to-end computing is a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers. When this framework is used as part of distributed cloud models, data and application at end nodes can be protected by confidential computing.

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