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 langua…(more)
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%0 Journal Article
%1 Juttner2023-vv
%A Jüttner, Victor
%A Grimmer, Martin
%A Buchmann, Erik
%D 2023
%K ChatGPT Detection Intrusion Networks Yaff
%T ChatIDS: Explainable Cybersecurity Using Generative AI
%X 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.
@article{Juttner2023-vv,
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.},
added-at = {2025-01-07T13:10:31.000+0100},
author = {J{\"u}ttner, Victor and Grimmer, Martin and Buchmann, Erik},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/20102168dadda947c294ee4bb0d6daa48/scadsfct},
eprint = {2306.14504},
interhash = {07e2df51bed39f1fac2b0c40b5fc1e38},
intrahash = {0102168dadda947c294ee4bb0d6daa48},
keywords = {ChatGPT Detection Intrusion Networks Yaff},
primaryclass = {cs.CR},
timestamp = {2025-02-04T11:07:50.000+0100},
title = {{ChatIDS}: Explainable Cybersecurity Using Generative {AI}},
year = 2023
}