Incident management in telecom and computer networks requires correlating and interpreting heterogeneous technical information sources. While knowledge graphs have proven flexible for data integration and logical reasoning, their use in network and cyber-security monitoring systems (NMS/SIEM) is not yet widespread. In this work, we explore the integration of knowledge graphs to facil-itate the diagnosis of complex situations from the perspective of NetOps/SecOps experts who use NMS/SIEMs. Through expert inter-views, we identify expectations in terms of ergonomics and decision support functions, and propose a Web-based client-server software architecture using an RDF knowledge graph that describes network systems and their dynamics. Based on a UI/UX evaluation and feed-back from a user panel, we demonstrate the need to go beyond simple data retrieval from the knowledge graph. We also highlight the importance of synergistic reasoning and interactive analysis of multi-layered systems. Overall, our work provides a foundation for future designs of knowledge-graph-based NMS/SIEM decision support systems with hybrid logical/probabilistic reasoning.
NORIA UI: Efficient incident management on large-scale ICT systems represented as knowledge graphs
ARES 2024, International Conference on Availability, Reliability and Security, track GRASEC (The 5th International Workshop on Graph-based Approaches for CyberSecurity), 30 July-2 August 2024, Vienna, Austria
Type:
Conference
City:
Vienna
Date:
2024-07-30
Department:
Data Science
Eurecom Ref:
7767
Copyright:
© ACM, 2024. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ARES 2024, International Conference on Availability, Reliability and Security, track GRASEC (The 5th International Workshop on Graph-based Approaches for CyberSecurity), 30 July-2 August 2024, Vienna, Austria https://doi.org/10.1145/3664476.3670438
See also:
PERMALINK : https://www.eurecom.fr/publication/7767