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Informationen zum Autor KARL OTS is Global Head of Cloud Security at EPAM Systems, an engineering and consulting firm. He leads a team of experts in delivering security and compliance solutions for cloud and AI deployments for Fortune 500 enterprises in a variety of industries. He has over 15 years' experience in tech and is a trusted advisor and thought leader. Karl is also a Microsoft Regional Director and Security MVP. Klappentext Securely harness the full potential of OpenAI's artificial intelligence tools in Azure Securing Microsoft Azure OpenAI is an accessible guide to leveraging the comprehensive AI capabilities of Microsoft Azure while ensuring the utmost data security. This book introduces you to the collaborative powerhouse of Microsoft Azure and OpenAI, providing easy access to cutting-edge language models like GPT-4o, GPT-3.5-Turbo, and DALL-E. Designed for seamless integration, the Azure OpenAI Service revolutionizes applications from dynamic content generation to sophisticated natural language translation, all hosted securely within Microsoft Azure's environment. Securing Microsoft Azure OpenAI demonstrates responsible AI deployment, with a focus on identifying potential harm and implementing effective mitigation strategies. The book provides guidance on navigating risks and establishing best practices for securely and responsibly building applications using Azure OpenAI. By the end of this book, you'll be equipped with the best practices for securely and responsibly harnessing the power of Azure OpenAI, making intelligent decisions that respect user privacy and maintain data integrity. Inhaltsverzeichnis Introduction xxiii Chapter 1 Overview of Generative Artificial Intelligence Security 1 Common Use Cases for Generative AI in the Enterprise 1 Generative Artificial Intelligence 1 Generative AI Use Cases 2 LLM Terminology 3 Sample Three-Tier Application 4 Presentation Tier 5 Application Tier 5 Data Tier 5 Generative AI Application Risks 5 Hallucinations 6 Malicious Usage 6 Shadow AI 7 Unfavorable Business Decisions 8 Established Risks 8 Shared AI Responsibility Model 8 Shared Responsibility Model for the Cloud 9 Shared Responsibility Model for AI 10 AI Usage 10 AI Application 10 AI Platform 11 Applying the Shared Responsibility Model 11 Regulation and Control Frameworks 12 Regulation in the United States 12 Regulation in the European Union 12 NIST AI Risk Management Framework 14 Govern 15 Map 15 Measure 16 Manage 16 Key Takeaways 16 References 17 Chapter 2 Security Controls for Azure OpenAI Service 19 On the Importance of Selecting Appropriate Security Controls 19 Risk Appetite 20 Comparing OpenAI Hosting Models 21 OpenAI ChatGPT 21 Privacy and Compliance 21 Identity and Access Management 21 Data Protection and Encryption 22 Audit Logging 22 Network Isolation 22 Data Residency 22 Azure OpenAI 22 Privacy and Compliance 23 Identity and Access Management 23 Data Protection and Encryption 23 Audit Logging 23 Network Isolation 23 Data Residency 23 Recommendation for Enterprise Usage 24 Evaluating Security Controls with MCSB 24 Control Domains 26 Network Security 27 Identity Management 28 Privileged Access 28 Data Protection 29 Asset Management 29 Logging and Threat Detection 29 Incident Response 30 Posture and Vulnerability Management 30 Endpoint Security 31 Backup and Recovery 31 DevOps Security 32 Governance and Strategy 32 Security Baselines 33 Applying Microsoft Cloud Secur...
