Extracting Cybersecurity Related Linked Data from Text
Year: 2013
Type: conference-paper
Abstract: The Web is typically our first source of information about new software vulnerabilities, exploits and cyber-attacks. Information is found in semi-structured vulnerability databases as well as in text from security bulletins, news reports, cyber security blogs and Internet chat rooms. It can be useful to cyber security systems if there is a way to recognize and extract relevant information and represent it as easily shared and integrated semantic data. We describe such an automatic framework that generates and publishes a RDF linked data representation of cyber security concepts and vulnerability descriptions extracted from the National Vulnerability Database and from text sources. A CRF-based system is used to identify cybersecurity-relatedentities, concepts and relations in text, which are then represented using custom ontologies for the cyber security domain and also mapped to objects in the DBpedia knowledge base. The resulting cyber security linked data collection can be used for many purposes, including automating early vulnerability identification, mitigation and prevention efforts.
DOI: 10.1109/icsc.2013.50
Authors: Arnav Joshi, Ravendar Lal, Tim Finin, Anupam Joshi
Language: English
Topic: Semantic Web and Ontologies
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1976339648