A Knowledge-Based Approach To Intrusion Detection Modeling

Simple item page
dc.contributor.authorMore, Sumit
dc.contributor.authorMathews, M. Lisa
dc.contributor.authorJoshi, Anupam
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-11-14T17:17:29Z
dc.date.available2018-11-14T17:17:29Z
dc.date.issued2012-05-24
dc.descriptionProceedings of the IEEE Workshop on Semantic Computing and Securityen_US
dc.description.abstractCurrent state of the art intrusion detection and prevention systems (IDPS) are signature-based systems that detect threats and vulnerabilities by cross-referencing the threat or vulnerability signatures in their databases. These systems are incapable of taking advantage of heterogeneous data sources for analysis of system activities for threat detection. This work presents a situation-aware intrusion detection model that integrates these heterogeneous data sources and build a semantically rich knowledge-base to detect cyber threats/vulnerabilities.en_US
dc.description.sponsorshipThis work was partially supported by a gift from Northrop Grumman Corporation and grant from Air Force Office of Scientific Research.en_US
dc.description.urihttps://ieeexplore.ieee.org/document/6227687en_US
dc.format.extent7 pagesen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/M2NC5SH1Z
dc.identifier.citationSumit More, M. Lisa Mathews, Anupam Joshi, and Tim Finin, A Knowledge-Based Approach To Intrusion Detection Modeling, Proceedings of the IEEE Workshop on Semantic Computing and Security, 2012, DOI: 10.1109/SPW.2012.26en_US
dc.identifier.uri10.1109/SPW.2012.26
dc.identifier.urihttp://hdl.handle.net/11603/11976
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rights© 2012 IEEE
dc.subjectsecurityen_US
dc.subjectvulnerabilityen_US
dc.subjectintrusion detectionen_US
dc.subjectinformation extractionen_US
dc.subjectontologyen_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleA Knowledge-Based Approach To Intrusion Detection Modelingen_US
dc.typeTexten_US

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
632.pd.pdf
Size:
199.46 KB
Format:
Adobe Portable Document Format
Description:
Download

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.68 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

UMBC Computer Science and Electrical Engineering Department
UMBC Faculty Collection
UMBC Student Collection