Confidential Computing: Protecting Data and Code in Use

Making Data Better

Jan 29 2024 • 37 mins

Data provides the basis for how we make decisions. An enemy of security these days, from our point of view, is plain text. We need better than that. We need device-assisted support for proving where data comes from and how it's been handled. We need systems that keep data (and code) from being altered without cause, that give us the ability to trace the change history of data.

Confidential computing is a new compute paradigm that provides a hardware-based foundation for running code and the data it manipulates. It safeguards data and code (it's all data; it's all code) in its most vulnerable state: while it's being processed.

In this episode of Making Data Better Steve and George are joined by Anjuna's Mark Bauer to dive into this new model's high impact on security and low impact on cloud app development.

Mark dissects the mechanics behind this approach including how it strengthens the software supply chain through hardware-based attestation. He addresses its fit in modern cloud infrastructure including Kubernetes, data loss prevention (DLP), API scanning and more.

The conversation addresses  the initial major use cases for confidential computing. High risk environments including defense, banking, and healthcare are obvious.  Not so obvious is securing multi-party data sets in the cloud for machine learning and AI-based applications.

So take a listen to this episode of Making Data Better and learn how hardware-based security can harden the cloud.

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