Speaker
Description
Recent Artificial Intelligence(AI) advancements, notably in Large Language Models(LLMs), have enhanced Natural Language Processing(NLP) capabilities like Text-to-SQL. Businesses are increasingly using LLMs for domain-specific applications such as chatbots, but this raises security concerns including data access control. This research addresses these concerns by developing a secure access control mechanism for Text-to-SQL applications. While there exists literature that aims to improve the technical aspects of Text-to-SQL systems, it lacks solutions for access control. This paper proposes a prototype integrating an access control layer within the Text-to-SQL process to ensure secure and authorized data access while maintaining usability and performance. The research is validated through the development of a domain-specific chatbot prototype that demonstrates its effectiveness in mitigating security related access control risks.
