Publications

An Ontology for Describing Security Events

Hossein Fani and Ebrahim Bagheri
Reference:
Links to Publication: [doi][www][pdf]
Abstract:
Mining security events helps with better precautionary planning for community safety. However, incident records are expressed in diverse and application dependent formats which impedes common comprehension for automatic knowledge extraction and reasoning. In this paper, we present Security Incident Ontology, SIO, a novel light-weight domain ontology for security incidents. We use Timeline to annotate the temporal facts of incidents and adopt Event to represent any security issues from indecent behavior to assault to more adverse crime which raise the security alarm in a community. It will present a unique way to the security incident detectors, a police officer, Robocops, or intelligent CCTV cameras, to report security events. We use SIO in populating security incident notifications of Integrated Risk Management (IRM) at Ryerson University to evaluate its competency, for Ryerson University campus has both business and housing area in the vicinity and encompass not only high rate, but also wide variety of different security issues. SIO is developed in OWL 2 with Protégé.
Bibtex Entry:
@inproceedings{DBLP:conf/seke/FaniB15, author = {Hossein Fani and Ebrahim Bagheri}, title = {An Ontology for Describing Security Events}, booktitle = {The 27th International Conference on Software Engineering and Knowledge Engineering, {SEKE} 2015, Wyndham Pittsburgh University Center, Pittsburgh, PA, USA, July 6-8, 2015}, pages = {455--460}, year = {2015}, crossref = {DBLP:conf/seke/2015}, url = {http://dx.doi.org/10.18293/SEKE2015-101}, doi = {10.18293/SEKE2015-101}, webpdf = {http://ls3.rnet.ryerson.ca/papers/An_Ontology_for_Describing_Security_Events-seke16.pdf}, timestamp = {Thu, 06 Aug 2015 19:20:08 +0200}, biburl = {http://dblp.uni-trier.de/rec/bib/conf/seke/FaniB15}, bibsource = {dblp computer science bibliography, http://dblp.org}, abstract = {Mining security events helps with better precautionary planning for community safety. However, incident records are expressed in diverse and application dependent formats which impedes common comprehension for automatic knowledge extraction and reasoning. In this paper, we present Security Incident Ontology, SIO, a novel light-weight domain ontology for security incidents. We use Timeline to annotate the temporal facts of incidents and adopt Event to represent any security issues from indecent behavior to assault to more adverse crime which raise the security alarm in a community. It will present a unique way to the security incident detectors, a police officer, Robocops, or intelligent CCTV cameras, to report security events. We use SIO in populating security incident notifications of Integrated Risk Management (IRM) at Ryerson University to evaluate its competency, for Ryerson University campus has both business and housing area in the vicinity and encompass not only high rate, but also wide variety of different security issues. SIO is developed in OWL 2 with Protégé.} }




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