Securing the Future of AI: Authorization Strategies for RAG Systems with LangChain4J and OpenFGA

Overview

Discover robust authorization frameworks for RAG systems using LangChain4J and OpenFGA, exploring RBAC and ReBAC implementation strategies to safeguard sensitive data while maintaining system efficiency.

Syllabus

- Introduction to RAG Systems -- Overview of Retrieval-Augmented Generation (RAG) systems -- Importance of security in AI applications -- Key challenges in authorizing RAG systems - Fundamentals of Authorization Frameworks -- Understanding Access Control models -- Comparison between RBAC (Role-Based Access Control) and ReBAC (Relationship-Based Access Control) - LangChain4J Overview -- Introduction to LangChain4J -- Key features and integration with RAG systems -- Security capabilities of LangChain4J - OpenFGA Overview -- Introduction to OpenFGA -- Architecture and components -- Authorization policies and enforcement - Implementing RBAC in RAG Systems -- Defining roles and permissions -- Integrating RBAC with LangChain4J -- Case study: Applying RBAC using OpenFGA - Implementing ReBAC in RAG Systems -- Understanding relationships in access control -- Integrating ReBAC with LangChain4J -- Case study: Applying ReBAC using OpenFGA - Best Practices for Authorization in RAG Systems -- Balancing security and efficiency -- Role hierarchy and relationship management -- Regular audits and monitoring - Advanced Topics -- Scalability of authorization frameworks -- Real-time authorization in high-throughput environments -- Future trends in AI security - Workshop and Hands-on Session -- Setting up a LangChain4J environment -- Defining and testing RBAC/RBAC rules with OpenFGA -- Troubleshooting common authorization issues - Course Summary and Next Steps -- Recap of key learnings -- Resources for continued learning -- Opportunities in AI security and authorization

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