Taxonomies using the clique percolation method for building a threats observatory

Romina Torres, Nicolás González, Mathías Cabrera, Rodrigo Salas

Resultado de la investigación: Contribución a los tipos de informe/libroContribución a la conferenciarevisión exhaustiva

Resumen

Cyberattacks are increasing every day, demanding that security incident response teams proactively determine potential threats early. Although social networks such as Twitter are a rich and up-to-date source of information where users use to tweet about different topics, it is complex to efficiently and effectively obtain results that support decision-making on a specific subject, such as cyberattacks. Therefore, in this work, we propose to use an offline mining process based on the clique percolation method over a corpus of tweets in order to generate an indexed knowledge base about cyberattacks. Results are promising to observe threats under evolution. Then, to show results properly, we generate an observatory prototype to allow cybersecurity researchers to explore threats over time and space.

Idioma originalInglés
Título de la publicación alojadaProceedings - 2021 47th Latin American Computing Conference, CLEI 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665495035
DOI
EstadoPublicada - 2021
Evento47th Latin American Computing Conference, CLEI 2021 - Virtual, Cartago, Costa Rica
Duración: 25 oct. 202129 oct. 2021

Serie de la publicación

NombreProceedings - 2021 47th Latin American Computing Conference, CLEI 2021

Conferencia

Conferencia47th Latin American Computing Conference, CLEI 2021
País/TerritorioCosta Rica
CiudadVirtual, Cartago
Período25/10/2129/10/21

Áreas temáticas de ASJC Scopus

  • Inteligencia artificial
  • Informática aplicada
  • Visión artificial y reconocimiento de patrones
  • Hardware y arquitectura
  • Educación

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