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19 TopicsPreview of Azure Confidential Clean Rooms for secure multiparty data collaboration
Today, we are excited to announce the preview of Azure Confidential Clean Rooms, a cutting-edge solution designed for organizations that require secure multi-party data collaboration. With Confidential Clean Rooms, you can share privacy sensitive data such as personally identifiable information (PII), protected health information (PHI) and cryptographic secrets confidently, thanks to robust trust guarantees that help ensure that your data remains protected throughout its lifecycle from other collaborators and from Azure operators. This secure data sharing is powered by confidential computing, which helps protect data in-use by performing computations in hardware-based, attested Trusted Execution Environments (TEEs). These TEEs help prevent unauthorized access or modification of application code and data during use. Organizations across industries need to perform multi-party data collaboration with business partners, outside organizations, and even within company silos to improve business outcomes and bolster innovation. Confidential Clean Rooms help derive true value from such collaborations by enabling granular and private data to be shared while providing safeguards on data exfiltration hence protecting the intellectual property of the organization and the privacy of its customers and addressing concerns around regulatory compliance. Whether you’re a data scientist looking to securely fine-tune your ML model with sensitive data from other organizations, or a data analyst wanting to perform secure analytics on joint data with your partner organizations, Confidential Clean Rooms will help you achieve the desired results. You can sign up for the preview here Key Features Secure Collaboration and Governance: Allows collaborators to create tamper-resistant contracts that contain the constraints which will be enforced by the clean room. Governance verifies validity of those constraints before allowing data to be released into clean rooms and helps generate tamper-resistant audit trails. This is made possible with the help of an implementation of the Confidential Consortium Framework CCF). Enhanced Data Privacy: Provides a sandboxed execution environment which allows only authorized workloads to execute and prevents any unauthorized network or IO operations from within the clean room. This helps keep your data secure throughout the workload execution. This is possible with the help of deploying clean rooms in confidential containers on Azure Container Instances (ACI) which provides container group level integrity with runtime enforcement of the same. Verifiable trust at each step with the help of cryptographic remote attestation forms the cornerstone of Confidential Clean Rooms. Salient Use Cases Azure Confidential Clean Rooms caters to use cases spanning multiple industries. Healthcare: For fine-tuning and inferencing with predictive healthcare machine-learning (ML) models and for joint data analysis for advancing pharmaceutical research. This can help protect the privacy of patients and intellectual property of organizations while demonstrating regulatory compliance. Finance: For financial fraud detection through analysis of combined data across banks and other financial institutions and for providing personalized offers to customers through secure analysis of transaction data and purchase data in retail outlets Media and Advertising: For improving marketing campaign effectiveness by combining data across advertisers, ad-techs, publishers and measurement firms for audience targeting and attribution and measurement Retail: For enhanced personalized marketing and improved inventory and supply chain management Government and Public Sector Organizations: For analysis of high security data across multiple government and public sector organizations to streamline benefits for citizens Customer Testimonials We are already partnering with several organizations to accelerate their secure multi-party collaboration journey with confidential clean rooms. Confidential computing in healthcare allows secure data processing within isolated environments, called 'clean rooms', protecting sensitive patient data during AI model development, validation and deployment. Apollo Hospitals uses Azure Confidential Clean Rooms to enhance data privacy, encrypt data, and securely train AI models. The benefits include secure collaboration, anonymized patient privacy, intellectual property protection, and enhanced cybersecurity. Apollo’s pilot with Confidential Clean Rooms showed promising results, and future efforts aim to scale secure AI solutions, ensuring patient safety, privacy, and compliance as the healthcare industry advances technologically. - Dr. Sujoy Kar, Chief Medical Information Officer and Vice President, Apollo Hospitals Azure Confidential Clean Rooms is a game changer to make collaborations on sensitive data both seamless and secure. When combined with Sarus, any data processing job is automatically analyzed using the most advanced privacy technology. Once validated, they are processed securely in Confidential Clean Rooms protecting both the privacy of data and the confidentiality of the analysis itself. This eliminates administrative overheads and makes it very easy to build advanced data processing pipelines. With our partner EY, we're already leveraging it to help international banks improve AML practices without compromising privacy. - Maxime Agostini, CEO & Cofounder of Sarus Read here to learn more about how Sarus is using Confidential Clean Rooms. As co-leaders on this Data Consortium Pilot, we are thrilled to be working with industry partners, Sarus and Microsoft, to drive this initiative forward. By combining Sarus’ privacy preserving technologies and Microsoft’s Azure Confidential Clean Rooms, not only does this project push the edge of technology innovation, but it strives to address a pivotal issue that affects us as Canadians. Through this work, we aim to help financial services organizations and regulators navigate the complexities of private and personal data sharing, without compromising the integrity of the data, and adhering to all relevant privacy regulations. For the purposes of this pilot, we are focusing our efforts on how this technology can play a pivotal role in helping better detect cases of human trafficking, however, we recognize that it can be used to help organizations for multiple other use cases, and cross industries, including health care and government & public sector. - Jessica Hansen, Privacy Partner EY Canada, and Dana Ohab, AI & Data Partner EY Canada Retrieval-Augmented Generation (RAG) applications accessing Large Language Models (LLMs) are common in private AI workflows, but managing secure access to sensitive data can be complex. SafeLiShare’s integration of its LLM Secure Data Proxy (SDP) with Azure Confidential Clean Rooms (ACCR) simplifies access control and token management. The joint solution helps ensure runtime security through advanced Public Key Infrastructure (PKI) and centralized policy management in Trusted Execution Environments (TEEs), enforcing strict access policies and admission controls to guarantee authorized access to sensitive data. This integration establishes trust bindings between the Identity Provider (IDP), applications, and data, safeguarding each layer without compromise. It also enables secure creation, sharing, and management of applications and data assets, ensuring compliance in high-performance AI environments. - Cynthia Hsieh, VP of Marketing, SafeLiShare Read here to learn more about how SafeLiShare is using Confidential Clean Rooms. Learn More Signup for the preview of Azure Confidential Clean Rooms Confidential Consortium Framework (CCF) Confidential containers on Azure Container Instances (ACI)Preview: New DCasv6 and ECasv6 confidential VMs based on 4th Generation AMD EPYC™ processors
You can get started deploying your software on these confidential VMs by signing up here. Additional security enhancements With the launch of the DCasv6 and ECasv6 confidential VM family – we support AES-256 memory encryption enabled by default. Additionally, we now offer our customers the capability to leverage key protection with Virtualization-based Security (VBS) in Windows. By enabling key protection in Windows CVMs, customers can protect keys in-use from Guest OS and applications. This key protection is enforced by CPU hardware. Faster performance for confidential workloads These new CVMs have demonstrated up to 25% improvement in various benchmarks compared to our previous generation of AMD-based confidential VMs. KT is leveraging Azure confidential computing to secure sensitive and regulated data from its telco business in the cloud. With new V6 CVM offerings in Korea Central Region, KT extends its use to help Korean customers with enhanced security requirements, including regulated industries, benefit from the highest data protection as well as the fastest performance by the latest AMD SEV-SNP technology through its Secure Public Cloud built with Azure confidential computing. - Woojin Jung, EVP, KT Corporation Worldwide Region Availability These CVMs will be gradually made available across all supported Azure regions and availability zones. Please use the sign-up form to indicate interest in participating in the gated preview and regional requirements. General purpose & Memory-intensive workloads Featuring general purpose optimized memory-to-vCPU ratios and support up to 96 vCPUs and 384 GiB RAM, the DCasv6-series delivers enterprise-grade performance. The DCasv6-series enables organizations to run sensitive workloads with hardware-based security guarantees, making them ideal for applications processing regulated or confidential data. For more memory demanding workloads, the new ECasv6-series offer high memory-to-vCPU ratios with increased scalability up to 96 vCPUs and 672 GiB of RAM. The ECasv6-series is ideal for memory-intensive enterprise applications offering nearly double the memory capacity of DCasv6. The ECasv6-series scales 672 GiB RAM with up to 96 vCPUs, making them ideal for memory intensive applications that exceed even the capabilities of the DCasv6 series. DCasv6 DCadsv6 ECasv6 ECadsv6 vCPU 2 - 96 2 - 96 2 - 96 2 - 96 Memory 8 - 384 8 - 384 16 - 672 16 - 672 Max local disk NA 75-600GiB NA 75-600GiB OS Support These CVMs support the following guest operating systems: Windows Server 2019, 2022, 2025, Windows 11, Ubuntu 22.04, Ubuntu 24.04, and RHEL 9.4. Endorsements from our customers The BMW Group relies on Azure confidential VMs powered by AMD EPYC processors to enable a Zero Trust environment with end-to-end encryption for our identity authentication system, allowing over 200,000 associates to collaborate on building the future of individual mobility. The solution was made possible in part due to the fact that AMD EPYC processor based confidential VMs do not require code changes to protect data in memory. Further, our testing of the newest generation of DCasv6 VMs has shown significant improvements in performance, and we look forward to seeing them go live on Azure. - BMW Group Having early access to Microsoft’s latest confidential VMs is a game-changer, offering enhanced security and performance. Our customers are pleased that they won’t have to adapt existing algorithms to take advantage of computing within the optimal CVM environment available in their computing region and selected within the EscrowAI platform. - Mary Beth Chalk, Co-founder & Chief Commercial Officer, BeeKeeperAI Anjuna is thrilled to be among the first to access Microsoft’s latest confidential VMs, powered by the newest version of the AMD SEV-SNP technology. Our ongoing partnership with Microsoft Azure provides us with early access to explore advanced security and performance features. This collaboration empowers joint Azure and Anjuna customers to leverage the newest Azure technologies from day one, enhanced by the capabilities of the Anjuna Seaglass platform. - Ofir Azoulay-Rozanes, Director of Product Management, Anjuna Security Sign up now for exclusive access Joining our exclusive preview program gives you an opportunity to work with the product team. To get started deploying your software on the latest confidential VMs sign up here.Unlocking the potential of Privacy-Preserving AI with Azure Confidential Computing on NVIDIA H100
Learn how Azure and NVIDIA enable high-performance privacy-preserving machine learning scenarios by augmenting Azure Confidential VMs with confidential computing enabled NVIDIA H100 GPUs20KViews0likes0CommentsWhat’s new: RHEL 9.3 support for AMD confidential VMs, temp disk encryption, new regions
We are thrilled to announce the RHEL 9.3 support for AMD confidential VMs, expansion of Azure Confidential VMs featuring AMD SEV-SNP technology to the following new regions: Italy North, Germany West Central and UAE North, temp disk encryption support and General Availability (GA) release of Azure Databricks support for AMD-based confidential VMs.Announcing: Microsoft moves $25 Billion in credit card transactions to Azure confidential computing
Microsoft is proud to showcase that customers in the financial sector can rely on public Azure to add confidentiality to provide secure and compliant payment solutions that meet or exceed industry standards. Microsoft is committed to hosting 100% of our payment services on Azure, just as we would expect our customers to do. Microsoft’s Commerce Financial Services (CFS) has completed a critical milestone by deploying a level 1 Payment Card Industry Data Security Standard (PCI-DSS) compliant credit card processing and vaulting solution, moving $25 Billion in annual credit card transactions to the public Azure cloud.NLP Inferencing on Confidential Azure Container Instance
Thanks to the advancements in the area of natural language processing using machine learning techniques & highly successful new-age LLMs from OpenAI, Google & Microsoft - NLP based modeling & inferencing are one of the top areas of customer interest. These are being widely used in almost all Microsoft products & there is also a huge demand from our customers to utilize these techniques in their business apps. Similarly, there is a demand for privacy preserving infrastructure to run such apps.Unlocking the Power of Serverless Confidential Computing in the Cloud
Discover the transformative power of Serverless Confidential Containers on Azure Container Instances (ACI) for industries like healthcare technology, fintech, and RegTech. This solution harnesses the benefits of serverless and confidential computing, ensuring robust data security while processing, compliance with regulations, and seamless deployment. Ideal for managing sensitive data, mitigating risks, and fostering trust and innovation in a cloud-based digital landscape..