About https://w3id.org/scholarlydata/inproceedings/eswc-2024-resource-36

Subject: https://w3id.org/scholarlydata/inproceedings/eswc-2024-resource-36Property: http://www.w3.org/1999/02/22-rdf-syntax-ns#typehttp://www.ontologydesignpatterns.org/ont/dul/DUL.owl#SocialObjecthttp://www.w3.org/2000/01/rdf-schema#Resourcehttp://www.ontologydesignpatterns.org/ont/dul/DUL.owl#InformationObjecthttp://www.ontologydesignpatterns.org/ont/dul/DUL.owl#Objecthttp://purl.org/spar/fabio/ProceedingsPaperhttp://www.w3.org/2002/07/owl#Thinghttps://w3id.org/scholarlydata/ontology/conference-ontology.owl#InProceedingsProperty: http://www.w3.org/2000/01/rdf-schema#labelNORIA-O: An Ontology for Anomaly Detection and Incident Management in ICT SystemsProperty: http://swrc.ontoware.org/ontology#abstractLarge-scale Information and Communications Technology (ICT) systems give rise to difficult situations such as handling cascading failures and detecting complex malicious activities occurring on multiple services and network layers. For network supervision, managing these situations while ensuring the high-standard quality of service and security requires a comprehensive view on how communication devices are interconnected and are performing. However, the information is spread across heterogeneous data sources which triggers information integration challenges. Existing data models enable to represent computing resources and how they are allocated. However, to date, there is no model to describe the inter-dependencies between the structural, dynamic, and functional aspects of a network infrastructure. In this paper, we propose the NORIA ontology that has been developed together with network and cybersecurity experts in order to describe an infrastructure, its events, diagnosis and repair actions performed during incident management. A use case describing a fictitious failure shows how this ontology can model complex situations and serve as a basis for anomaly detection and root cause analysis. The ontology is available at https://w3id.org/noria and empowers the largest telco operator in France.Property: http://purl.org/dc/elements/1.1/creatorhttps://w3id.org/scholarlydata/person/lionel-tailhardathttps://w3id.org/scholarlydata/person/raphael-troncyhttps://w3id.org/scholarlydata/person/yoan-chabotProperty: http://purl.org/dc/elements/1.1/subjectNORIAIncident ManagementNetwork InfrastructureOntologyProperty: http://purl.org/dc/elements/1.1/titleNORIA-O: An Ontology for Anomaly Detection and Incident Management in ICT SystemsProperty: http://purl.org/ontology/bibo/authorListhttps://w3id.org/scholarlydata/authorlist/eswc-2024-resource-36Property: http://xmlns.com/foaf/0.1/makerhttps://w3id.org/scholarlydata/person/yoan-chabothttps://w3id.org/scholarlydata/person/raphael-troncyhttps://w3id.org/scholarlydata/person/lionel-tailhardatProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#abstractLarge-scale Information and Communications Technology (ICT) systems give rise to difficult situations such as handling cascading failures and detecting complex malicious activities occurring on multiple services and network layers. For network supervision, managing these situations while ensuring the high-standard quality of service and security requires a comprehensive view on how communication devices are interconnected and are performing. However, the information is spread across heterogeneous data sources which triggers information integration challenges. Existing data models enable to represent computing resources and how they are allocated. However, to date, there is no model to describe the inter-dependencies between the structural, dynamic, and functional aspects of a network infrastructure. In this paper, we propose the NORIA ontology that has been developed together with network and cybersecurity experts in order to describe an infrastructure, its events, diagnosis and repair actions performed during incident management. A use case describing a fictitious failure shows how this ontology can model complex situations and serve as a basis for anomaly detection and root cause analysis. The ontology is available at https://w3id.org/noria and empowers the largest telco operator in France.Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#hasAuthorListhttps://w3id.org/scholarlydata/authorlist/eswc-2024-resource-36Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#isPartOfhttps://w3id.org/scholarlydata/conference/eswc/2024/proceedingsProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#keywordOntologyNORIANetwork InfrastructureIncident ManagementProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#titleNORIA-O: An Ontology for Anomaly Detection and Incident Management in ICT Systems
Subject: https://w3id.org/scholarlydata/person/raphael-troncyProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/eswc-2024-resource-36
Subject: https://w3id.org/scholarlydata/conference/eswc/2024/proceedingsProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#hasParthttps://w3id.org/scholarlydata/inproceedings/eswc-2024-resource-36
Subject: https://w3id.org/scholarlydata/person/lionel-tailhardatProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/eswc-2024-resource-36
Subject: https://w3id.org/scholarlydata/role-during-event/eswc2024-author-lionel-tailhardat-eswc-2024-resource-36Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#withDocumenthttps://w3id.org/scholarlydata/inproceedings/eswc-2024-resource-36
Subject: https://w3id.org/scholarlydata/role-during-event/eswc2024-author-raphael-troncy-eswc-2024-resource-36Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#withDocumenthttps://w3id.org/scholarlydata/inproceedings/eswc-2024-resource-36
Subject: https://w3id.org/scholarlydata/role-during-event/eswc2024-author-yoan-chabot-eswc-2024-resource-36Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#withDocumenthttps://w3id.org/scholarlydata/inproceedings/eswc-2024-resource-36
Subject: https://w3id.org/scholarlydata/person/yoan-chabotProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/eswc-2024-resource-36