Deep Analysis and Detection of Firewall Anomalies Using Knowledge Graph

Abdelrahman Elfaki, Amer Aljaedi

2023

Abstract

Implementing firewall policy with defining firewall rules is a cumulative process that could take place in different periods and depend on the network conditions, which makes it prone to errors and difficult to validate without effective tools. Such tools should be carefully designed to capture and spot firewall configuration errors and anomalies. The solution in this paper consists of four steps, which are: formalizing the firewall rules by using FOL, defining the general form of the anomaly, collecting all active destinations’ IP addresses and port numbers in updated lists, and applying the proposed FOL rules for detecting firewall anomalies. The general form has been represented by using knowledge graph for supporting visualization aiming to detect firewall anomalies by extracting knowledge from the knowledge graph and its formalization rules. The proposed method is efficient and capable of discovering all types of firewall anomalies.

Paper Citation

in Harvard Style

Elfaki A. and Aljaedi A. (2023). Deep Analysis and Detection of Firewall Anomalies Using Knowledge Graph. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-626-2, pages 411-417. DOI: 10.5220/0011704900003411

in Bibtex Style

@conference{icpram23,
author={Abdelrahman Elfaki and Amer Aljaedi},
title={Deep Analysis and Detection of Firewall Anomalies Using Knowledge Graph},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2023},
pages={411-417},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011704900003411},
isbn={978-989-758-626-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Deep Analysis and Detection of Firewall Anomalies Using Knowledge Graph
SN - 978-989-758-626-2
AU - Elfaki A.
AU - Aljaedi A.
PY - 2023
SP - 411
EP - 417
DO - 10.5220/0011704900003411