Combating Fake Cyber Threat Intelligence using Provenance in Cybersecurity Knowledge Graphs

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dc.contributor.authorMitra, Shaswata
dc.contributor.authorPiplai, Aritran
dc.contributor.authorMittal, Sudip
dc.contributor.authorJoshi, Anupam
dc.date.accessioned2022-08-18T22:33:07Z
dc.date.available2022-08-18T22:33:07Z
dc.date.issued2022-01-13
dc.description.abstractToday there is a significant amount of fake cybersecurity related intelligence on the internet. To filter out such information, we build a system to capture the provenance information and represent it along with the captured Cyber Threat Intelligence (CTI). In the cybersecurity domain, such CTI is stored in Cybersecurity Knowledge Graphs (CKG). We enhance the exiting CKG model to incorporate intelligence provenance and fuse provenance graphs with CKG. This process includes modifying traditional approaches to entity and relation extraction. CTI data is considered vital in securing our cyberspace. Knowledge graphs containing CTI information along with its provenance can provide expertise to dependent Artificial Intelligence (AI) systems and human analysts.en_US
dc.description.sponsorshipThis work was supported by a U.S. Department of Defense grant and National Science Foundation grant #2133190.en_US
dc.description.urihttps://ieeexplore.ieee.org/document/9671867en_US
dc.format.extent8 pagesen_US
dc.genrejournal articlesen_US
dc.genrepreprintsen_US
dc.identifierdoi:10.13016/m2otqh-m4wz
dc.identifier.citationA. Piplai, S. Mittal, A. Joshi, T. Finin, J. Holt and R. Zak, "Creating Cybersecurity Knowledge Graphs From Malware After Action Reports," in IEEE Access, vol. 8, pp. 211691-211703, 2020, doi: 10.1109/ACCESS.2020.3039234.en_US
dc.identifier.urihttps://doi.org/10.1109/BigData52589.2021.9671867
dc.identifier.urihttp://hdl.handle.net/11603/25497
dc.language.isoen_USen_US
dc.publisherIEEEen_US
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.relation.ispartofUMBC Student Collection
dc.rights© 2022 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleCombating Fake Cyber Threat Intelligence using Provenance in Cybersecurity Knowledge Graphsen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0001-9151-8347en_US
dcterms.creatorhttps://orcid.org/0000-0002-8641-3193en_US

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