A Knowledge-Based Approach To Intrusion Detection Modeling

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https://ieeexplore.ieee.org/document/6227687

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10.1109/SPW.2012.26
 http://hdl.handle.net/11603/11976

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

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Date

2012-05-24

Type of Work

conference papers and proceedings preprints
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Citation of Original Publication

Sumit 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.2012.26

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© 2012 IEEE

Subjects

security
vulnerability
intrusion detection
information extraction
ontology
UMBC Ebiquity Research Group

Abstract

Current 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.