Towards a Relation Extraction Framework for Cyber-Security Concepts

Conference · Thu Jan 01 00:00:00 EST 2015

OSTI ID:1185925

Jones, Corinne L ^[1]; Bridges, Robert A ^[1]; Huffer, Kelly M ^[1]; Goodall, John R ^[1]

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1. ORNL

In order to assist security analysts in obtaining information pertaining to their network, such as novel vulnerabilities, exploits, or patches, information retrieval methods tailored to the security domain are needed. As labeled text data is scarce and expensive, we follow developments in semi-supervised NLP and implement a bootstrapping algorithm for extracting security entities and their relationships from text. The algorithm requires little input data, specifically, a few relations or patterns (heuristics for identifying relations), and incorporates an active learning component which queries the user on the most important decisions to prevent drifting the desired relations. Preliminary testing on a small corpus shows promising results, obtaining precision of .82.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: Work for Others (WFO)
• DOE Contract Number: DE-AC05-00OR22725
• OSTI ID: 1185925
• Resource Relation: Conference: CISRC 2015, Oak Ridge, TN, USA, 20150408, 20150409
• Country of Publication: United States
• Language: English