  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.
