Temporal Understanding of Cybersecurity Threats

dc.contributor.authorSleeman, Jennifer
dc.contributor.authorFinin, Tim
dc.contributor.authorHalem, Milton
dc.date.accessioned2020-07-22T16:05:51Z
dc.date.available2020-07-22T16:05:51Z
dc.date.issued2020-06-23
dc.description2020 IEEE 6th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), 25-27 May 2020, Baltimore, MD, USA, USAen
dc.description.abstractAs cybersecurity-related threats continue to increase, understanding how the field is changing over time can give insight into combating new threats and understanding historical events. We show how to apply dynamic topic models to a set of cybersecurity documents to understand how the concepts found in them are changing over time. We correlate two different data sets, the first relates to specific exploits and the second relates to cybersecurity research. We use Wikipedia concepts to provide a basis for performing concept phrase extraction and show how using concepts to provide context improves the quality of the topic model. We represent the results of the dynamic topic model as a knowledge graph that could be used for inference or information discovery.en
dc.description.urihttps://ieeexplore.ieee.org/document/9123059en
dc.format.extent7 pagesen
dc.genreconference papers and proceedings preprintsen
dc.identifierdoi:10.13016/m2v88o-bcfw
dc.identifier.citationJ. Sleeman, T. Finin and M. Halem, "Temporal Understanding of Cybersecurity Threats," 2020 IEEE 6th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), Baltimore, MD, USA, 2020, pp. 115-121, doi: 10.1109/BigDataSecurity-HPSC-IDS49724.2020.00030.en
dc.identifier.uri10.1109/BigDataSecurity-HPSC-IDS49724.2020.00030
dc.identifier.urihttp://hdl.handle.net/11603/19214
dc.language.isoenen
dc.publisherIEEEen
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.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© 2020 IEEE
dc.subjectUMBC Ebiquity Research Group
dc.titleTemporal Understanding of Cybersecurity Threatsen
dc.typeTexten

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