Leipzig, 09/28/2017 – Microsoft Azure is the first cloud to offer new data security capabilities with a collection of features and services called Azure confidential computing. Put simply, confidential computing offers a protection that to date has been missing from public clouds, encryption of data while in use. This means that data can be processed in the cloud with the assurance that it is always under customer control.
Data breaches are virtually daily news events, with attackers gaining access to personally identifiable information (PII), financial data, and corporate intellectual property. While many breaches are the result of poorly configured access control, most can be traced to data that is accessed while in use, either through administrative accounts, or by leveraging compromised keys to access encrypted data. Despite advanced cybersecurity controls and mitigations, some customers are reluctant to move their most sensitive data to the cloud for fear of attacks against their data when it is in-use. With confidential computing, they can move the data to Azure knowing that it is safe not only at rest, but also in use from the following threats:
Malicious insiders with administrative privilege or direct access to hardware on which it is being processed
Hackers and malware that exploit bugs in the operating system, application, or hypervisor
Third parties accessing it without their consent
Confidential computing ensures that when data is “in the clear,” which is required for efficient processing, the data is protected inside a Trusted Execution Environment (TEE - also known as an enclave).
Azure Confidential Computing (Source: Microsoft)
Azure confidential computing is highly interesting for many industries including finance, healthcare, AI, and beyond. In finance, for example, personal portfolio data and wealth management strategies would no longer be visible outside of a TEE. 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. In oil and gas, and IoT scenarios, sensitive seismic data that represents the core intellectual property of a corporation can be moved to the cloud for processing, but with the protections of encrypted-in-use technology.
If you are interested in Azure confidential computing, consider signing up for the Early Access program.
Read the full announcement here.
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