RT Journal Article
T1 Methodological Framework to Collect, Process, Analyze and Visualize Cyber Threat Intelligence Data
A1 Borges Amaro, Lucas José
A1 Percilio Azevedo, Bruce William
A1 Lopes de Mendonca, Fabio Lucio
A1 Ferreira Giozza, William
A1 Oliveira Albuquerque, Robson de
A1 García Villalba, Luis Javier
AB Cyber attacks have increased in frequency in recent years, affecting small, medium and large companies, creating an urgent need for tools capable of helping the mitigation of such threats. Thus, with the increasing number of cyber attacks, we have a large amount of threat data from heterogeneous sources that needs to be ingested, processed and analyzed in order to obtain useful insights for their mitigation. This study proposes a methodological framework to collect, organize, filter, share and visualize cyber-threat data to mitigate attacks and fix vulnerabilities, based on an eight-step cyber threat intelligence model with timeline visualization of threats information and analytic data insights. We developed a tool to address needs in which the cyber security analyst can insert threat data, analyze them and create a timeline to obtain insights and a better contextualization of a threat. Results show the facilitation of understanding the context in which the threats are inserted, rendering the mitigation of vulnerabilities more effective.
PB MPDI
SN 2076-3417
YR 2022
FD 2022-01-24
LK https://hdl.handle.net/20.500.14352/72082
UL https://hdl.handle.net/20.500.14352/72082
LA eng
NO Unión Europea. Horizonte 2020
DS Docta Complutense
RD 13 abr 2025