Microsoft Unveils Azure Confidential Computing for Secure Cloud Data Processing
15 Septembre, 2017, 06:21 | Author: Come Portier
From strict physical datacenter security, ensuring data privacy, encrypting data at rest and in transit, novel uses of machine learning for threat detection, and the use of stringent operational software development lifecycle controls, Azure represents the cutting edge of cloud security and privacy.
Known as Azure Confidential Computing, the service is now in an early access test and aims to provide security for cloud data while it is in use by cloud applications. The Azure team, along with Microsoft Research, Intel, Windows, and our Developer Tools group, have been working on confidential computing software and hardware technologies for over four years. The protected, TEE parts will run in a separate virtual machine containing only a basic stub operating system (enough that it can communicate with the regular VM) and only those parts of the application code that need to handle the sensitive data. They even ensure that only authorized code is permitted to access data. If the code is tampered with, the operations are denied and the TEE is disabled, Microsoft said. Code and data that are inside a TEE can not be inspected from outside the TEE. Only those with a special access code will be allowed access to the data within the TEE. At present, Azure confidential computing supports two TEEs, one software-based, and the other hardware-based. The first is the software-based Virtual Secure Mode found in the Hyper-V virtualization software components in Windows Server 2016 and Windows 10. In this instance, Hyper-V prevents the running of administrator code on either the computer or server, as well as the viewing of content and modification of its execution within the VSM enclave. The Redmond giant has also implemented them in its Coco Framework, geared towards enterprise blockchain use. Put simply, confidential computing offers a protection that to date has been missing from public clouds, encryption of data while in use. Healthcare organizations can collaborate by sharing their private patient data, like genomic sequences, to gain deeper insights from machine learning across multiple data sets without risk of data being leaked to other organizations. "This next level of "encryption in use" will help customers further protect their data", the company said in a statement. If you are interested in Azure confidential computing Early Access, sign up here.
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