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7 TopicsPrice reduction and upcoming features for Azure confidential ledger!
Effective March 1, 2025, you can keep your records in Azure confidential ledger (ACL) at the reduced price of ~$3/day per instance! The reduced price is for the computation and the ledger use. The price of any additional storage used will remain unchanged. To tamper protect your records: Automatically create hash (e.g. MD5 or SHA256) of your blob storage data and keep those in Azure confidential ledger. For forensics, you can verify the integrity of the data against the signature in ACL. Imagine doing this as you are migrating data from one system to another, or when you restore archived records from cold storage. It is also valuable when there is a need to protect from insider/administrator risks and confidently report to authorities. If you keep your data in Azure SQL database, you can use their security ledger feature to auto generate record digests and store them in confidential ledger for integrity protection and safeguarding. You can use the SQL stored procedure to verify that no tampering or administrator modifications occurred to your SQL data! In addition, we are announcing the preview of User Defined Functions for Azure confidential ledger. Imagine doing a schema validation before writing data to the Ledger or using pattern matching to identify sensitive information in log messages and perform data massaging to mask it. To increase your awareness, request access for this preview via the sign-up form. Get started by reading our documentation and trying out confidential ledger yourself! _____________________________________________________________________________________________________ What is Azure confidential ledger and what is the change? It is a tamper protected and auditable data store backed by a Merkle tree blockchain structure for sensitive records that require high levels of integrity protection and/or confidentiality. While customers from AI, financial services, healthcare, and supply chain continue to use the ledger for their business transaction’s archival needs and confidential data’s unique identifiers for audit purposes, we are acting on their feedback for scaling ledgers to more of their workloads with a more competitive price! How can I use Azure confidential ledger? - Azure SQL database ledger customers can enable confidential ledger as its trusted digest store to uplevel integrity and security protection posture - Azure customers who use blob storage have found value in migrating their workloads to Azure with a tamper protection check via the Azure confidential ledger Marketplace App. - Azure customers who use data stores and databases (e.g. Kusto, Cosmos, and Log Analytics) may benefit from auditability and traceability of logs being kept in the confidential ledger with new compliance certifications in SOC 2 Type 2 and ISO27001. How much does Azure confidential ledger cost? - Approximately $3/day/ledger _____________________________________________________________________________________________________ Resources Explore the Azure confidential ledger documentation Read the blog post on: Integrity protect blob storage Read the blog post on: How to choose between ledger in Azure SQL Database and Azure Confidential Ledger Read the blog post on: Verify integrity of data transactions in Azure confidential ledger View our recent webinar in the Security Community Recent case studies: HB Antwerp & BeekeeperAI566Views0likes0CommentsPreview 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)Announcing the Public Preview of Azure Managed Confidential Consortium Framework
Customers and partners have expressed that they require: * customizable governance across multiple parties that works even when some members depart, * transparency and auditability to see what data is being read and acted on, confidentiality to have end-to-end technical protection when dealing with sensitive data, * resiliency in scalable, performant infrastructure for enterprise capabilities, and * developer friendly experience that has ease-of-use and does not require specialized development teams. To provide a solution that addresses these needs, we are announcing the public preview of Azure Managed Confidential Consortium Framework – a collaboration platform for decentralized trust and governance application development.Try new Azure confidential ledger features, including an Azure Blob Storage Marketplace application
To support customers in regulated industries and compliance scenarios who asked about higher integrity protection of storage blobs, the Azure confidential ledger team has launched a preview of a managed Marketplace application that will further protect data: Blob Storage Digests Backed by Confidential Ledger (Preview)..... The Azure confidential ledger team has also launched new features to enhance product and auditing experience: The Azure confidential ledger Portal experience has been improved with a new Ledger Explorer feature that allows observing transactions and validating the cryptographic proofs of ledger transactions...3.2KViews2likes0CommentsAzure confidential ledger is now Generally Available!
I am pleased to announce that Azure confidential ledger is now generally available! Azure confidential ledger is an unstructured, trusted data store for important identifiers of sensitive data that require high integrity. Data records stored on Azure confidential ledger remain immutable (i.e. Write Once, Read Many) and can be cryptographically verified. It offers a simple experience with REST APIs that can be easily integrated into the application architecture.13KViews4likes0CommentsGetting started with portal for Azure confidential ledger
Earlier this year, Azure confidential ledger, a managed service for keeping sensitive records intact for perpetuity with high integrity, became available to customers in preview with Python and ARM quickstarts. To build on this, today, we are excited to announce the portal experience to create your confidential ledgers!3.1KViews0likes0CommentsChoosing an Azure Ledger Technology
At the annual Microsoft Build 2021 Developer Conference, we announced two new products that are based on blockchain technology. Azure Confidential Ledger, now in preview, offers a fully managed service for customers who need to store sensitive data with high integrity and confidentiality. Azure SQL Database ledger, also in preview, enables storage of sensitive relational data in a tamper-evident way.3.9KViews0likes0Comments