Abstract

Topic modeling algorithms from the natural language processing (NLP) discipline have been used for various applications. For instance, topic modeling for the product recommendation systems in the e-commerce systems. In this paper, we briefly reviewed topic modeling applications and then described our proposed idea of utilizing topic modeling approaches for cyber threat intelligence (CTI) applications. We improved the previous work by implementing BERTopic and Top2Vec approaches, enabling users to select their preferred pre-trained text/sentence embedding model, and supporting various languages. We implemented our proposed idea as the new topic modeling module for the Open Web Application Security Project (OWASP) Maryam: Open-Source Intelligence (OSINT) framework. We also described our experiment results using a leaked hacker forum dataset (nulled.io) to attract more researchers and open-source communities to participate in the Maryam project of OWASP Foundation.

Original languageEnglish
Title of host publication2022 7th International Conference on Informatics and Computing, ICIC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350345711
DOIs
Publication statusPublished - 2022
Event7th International Conference on Informatics and Computing, ICIC 2022 - Virtual, Online, Indonesia
Duration: 8 Dec 20229 Dec 2022

Publication series

Name2022 7th International Conference on Informatics and Computing, ICIC 2022

Conference

Conference7th International Conference on Informatics and Computing, ICIC 2022
Country/TerritoryIndonesia
CityVirtual, Online
Period8/12/229/12/22

Keywords

  • Maryam
  • OWASP
  • cyber threat intelligence
  • threat recommendation
  • topic modeling

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