Automatic Summarization of Validated Intelligence Events

dc.contributor.authorBECERRA, TEO
dc.contributor.authorJOHANSSON, LINUS
dc.contributor.departmentChalmers tekniska högskola / Institutionen för data och informationstekniksv
dc.contributor.departmentChalmers University of Technology / Department of Computer Science and Engineeringen
dc.contributor.examinerRichard, Johansson
dc.contributor.supervisorNorlund, Tobias
dc.date.accessioned2023-12-19T14:50:37Z
dc.date.available2023-12-19T14:50:37Z
dc.date.issued2023
dc.date.submitted2023
dc.description.abstractIn recent years there have been enormous progress and breakthroughs in the field of natural language processing (NLP). These breakthroughs have significantly advanced the state-of-the-art in NLP across the board and there have been a growing interest to apply these findings in an industrial setting. This thesis work is carried out in collaboration with Recorded Future, that has an interest in whether large language models can produce Validated Intelligence Event (VIE) summaries of high quality. A VIE summary is an analytical offering that describes an event in the cybersecurity domain and if these could be automatically generated it would allow for higher throughput of such summaries and would generate more value for their clients. Our results show that such summaries are possible to produce with relatively high performance, even though they cannot be completely automated with the techniques used in this paper. However, the analysts who are currently producing these summaries expect that the use of an automated system such as this can decrease the production time by 4.
dc.identifier.coursecodeDATX05
dc.identifier.urihttp://hdl.handle.net/20.500.12380/307441
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectNLP
dc.subjectGPT-3
dc.subjectPRIMERA
dc.subjectabstractive summarization
dc.subjectextractive summarization
dc.subjecthallucination
dc.titleAutomatic Summarization of Validated Intelligence Events
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster's Thesisen
dc.type.uppsokH
local.programmeComputer science – algorithms, languages and logic (MPALG), MSc
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