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Leveraging OSINT to improve threat intelligence quality

datacite.subject.fosDepartamento de Informáticapt_PT
dc.contributor.advisorMedeiros, Ibéria Vitória de Sousa, 1971-
dc.contributor.advisorBessani, Alysson Neves, 1978-
dc.contributor.authorAzevedo, Rui Correia Neves Cordeiro de
dc.date.accessioned2019-02-27T10:36:54Z
dc.date.available2019-02-27T10:36:54Z
dc.date.issued2019
dc.date.submitted2019
dc.descriptionTese de mestrado, Segurança Informática, Universidade de Lisboa, Faculdade de Ciências, 2019pt_PT
dc.description.abstractThe Impact of cyber-attacks and its cost has become a top priority for most organizations. To more aptly protect themselves, organizations are moving from reactive to proactive defensive measures, investing in cyber threat intelligence (CTI) to provide them forewarning about the risks they face, as well as to accelerate their response times in the detection of attacks. One means to obtain CTI is the collection of open source intelligence (OSINT) feeds via threat intelligence platforms and their representation as indicators of compromise (IoC). However, most of these platforms are providing threat information with little to no processing. This Situation increases the pressure on security analysts who, already faced with the arduous task of sorting through the multitude of alerts originating from their networks must also sort this additional flow of data to find relevant intelligence.This dissertation proposes an architecture to generate threat intelligence of quality in the form of new intelligence is obtained by correlating IoCs coming from different OSINT feeds that contain information on the same threat, aggregation them into clusters, and then representing the threat information contained within those clusters in a single enriched IoC. This dissertation first offers an overview of the use of CTI, methodologies, and technologies used, before proposing an architecture focused on a clustering approach, for which two methods are introduced, the naïve and the n-level aggregation. It then describes the implementation of this architecture and its validation. The proposal was implemented in a prototype confirmed with 34 OSINT feeds, which allowed the creation of enriched IoCs that may enable the identification of cyber-attacks not previously possible by analyzing the received IoCs individually.pt_PT
dc.identifier.tid202195929
dc.identifier.urihttp://hdl.handle.net/10451/37202
dc.language.isoengpt_PT
dc.subjectCibersegurançapt_PT
dc.subjectOpen source intelligence (OSINT)pt_PT
dc.subjectInformações de fonte abertapt_PT
dc.subjectPlataforma de partilha de informação sobre ameaçaspt_PT
dc.subjectIndicadores de comprometimentopt_PT
dc.subjectSegurançapt_PT
dc.subjectTeses de mestrado - 2019pt_PT
dc.titleLeveraging OSINT to improve threat intelligence qualitypt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameMestrado em Segurança Informáticapt_PT

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