CASIE: Extracting Cybersecurity Event Information from Text

dc.contributor.authorSatyapanich, Taneeya
dc.contributor.authorFerraro, Francis
dc.contributor.authorFinin, Tim
dc.date.accessioned2020-02-03T15:14:58Z
dc.date.available2020-02-03T15:14:58Z
dc.date.issued2020-02
dc.description34th AAAI Confference on Artificial Intelligence, New York, Feb. 2020en_US
dc.description.abstractWe present CASIE, a system that extracts information about cybersecurity events from text and populates a semantic model, with the ultimate goal of integration into a knowledge graph of cybersecurity data. It was trained on a new corpus of 1,000 English news articles from 2017–2019 that are labeled with rich, event-based annotations and that covers both cyberattack and vulnerability-related events. Our model defines five event subtypes along with their semantic roles and 20 event-relevant argument types (e.g., file, device, software, money). CASIE uses different deep neural networks approaches with attention and can incorporate rich linguistic features and word embeddings. We have conducted experiments on each component in the event detection pipeline and the results show that each subsystem performs well.en_US
dc.description.sponsorshipPartial support for this research was provided by a gift from the IBM AI Horizons Network.en_US
dc.format.extent9 pagesen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/m2002f-k9wr
dc.identifier.citationSatyapanich, Taneeya; Ferraro, Francis; Finin, Tim; CASIE: Extracting Cybersecurity Event Information from Text; 34th AAAI Confference on Artificial Intelligence, New York, Feb. 2020; https://ebiquity.umbc.edu/_file_directory_/papers/943.pdfen_US
dc.identifier.urihttp://hdl.handle.net/11603/17206
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofUMBC Faculty 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.titleCASIE: Extracting Cybersecurity Event Information from Texten_US
dc.typeTexten_US

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