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ChatIDS: Explainable Cybersecurity Using Generative AI

Authors:
Victor Jüttner
Martin Grimmer
Erik Buchmann

Keywords: Intrusion Detection; ChatGPT; Networks

Abstract:
Intrusion Detection Systems (IDS) are a proven approach to secure networks. However, in a privately used network, it is difficult for users without cybersecurity expertise to understand IDS alerts, and to respond in time with adequate measures. This puts the security of home networks, smart home installations, home-office workers, etc. at risk, even if an IDS is correctly installed and configured. In this work, we propose ChatIDS, our approach to explain IDS alerts to non-experts by using large language models. We evaluate the feasibility of ChatIDS by using ChatGPT, and we identify open research issues with the help of interdisciplinary experts in artificial intelligence. Our results show that ChatIDS has the potential to increase network security by proposing meaningful security measures in an intuitive language from IDS alerts. Nevertheless, some potential issues in areas such as trust, privacy, ethics, etc. need to be resolved, before ChatIDS might be put into practice.

Pages: 7 to 10

Copyright: Copyright (c) IARIA, 2023

Publication date: September 25, 2023

Published in: conference

ISSN: 2162-2116

ISBN: 978-1-68558-092-6

Location: Porto, Portugal

Dates: from September 25, 2023 to September 29, 2023