AuditNet: A Conversational AI-based Security Assistant [DEMO]
Shohreh Deldari, Mohammad Goudarzi, Aditya Joshi, Arash Shaghaghi,, Simon Finn, Flora D. Salim, Sanjay Jha

TL;DR
AuditNet is a novel conversational AI framework that automates compliance verification across various domains by leveraging retrieval-augmented generation, reducing manual effort and improving accuracy for professionals.
Contribution
This paper introduces AuditNet, the first conversational AI security assistant tailored for IoT network security experts, integrating retrieval-augmented generation for compliance checking.
Findings
Automates compliance review process using AI.
Enhances accuracy and efficiency in security standards adherence.
Supports instant access to security policies and regulations.
Abstract
In the age of information overload, professionals across various fields face the challenge of navigating vast amounts of documentation and ever-evolving standards. Ensuring compliance with standards, regulations, and contractual obligations is a critical yet complex task across various professional fields. We propose a versatile conversational AI assistant framework designed to facilitate compliance checking on the go, in diverse domains, including but not limited to network infrastructure, legal contracts, educational standards, environmental regulations, and government policies. By leveraging retrieval-augmented generation using large language models, our framework automates the review, indexing, and retrieval of relevant, context-aware information, streamlining the process of verifying adherence to established guidelines and requirements. This AI assistant not only reduces the manual…
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Taxonomy
TopicsBig Data and Business Intelligence · Network Security and Intrusion Detection
