Cybersecurity Text Data Classification and Optimization for CTI Systems

Ariel Rodriguez, Koji Okamura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Cyber threat intelligence systems provide a way to prioritize alerts and allow security teams to focus on critical threats and utilize their resources more efficiently. One challenge in these systems comes in accurately classifying the data that is input and processed within the system which is critical to producing meaningful output. To tackle this problem, in this paper we research text-based cybersecurity data classification methods using a multi-layer keyword filtering method and unsupervised learning methods using doc2vec. We also look at how we can optimize the accuracy and efficiency of cyber threat intelligence systems through the use of ensemble learning. This research will help with prioritization of cyber threat intelligence systems which allow security teams to use their resources more efficiently.

Original languageEnglish
Title of host publicationWeb, Artificial Intelligence and Network Applications - Proceedings of the Workshops of the 34th International Conference on Advanced Information Networking and Applications, WAINA 2020
EditorsLeonard Barolli, Flora Amato, Francesco Moscato, Tomoya Enokido, Makoto Takizawa
PublisherSpringer
Pages410-419
Number of pages10
ISBN (Print)9783030440374
DOIs
Publication statusPublished - 2020
EventWorkshops of the 34th International Conference on Advanced Information Networking and Applications, WAINA 2020 - Caserta, Italy
Duration: Apr 15 2020Apr 17 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1150 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceWorkshops of the 34th International Conference on Advanced Information Networking and Applications, WAINA 2020
Country/TerritoryItaly
CityCaserta
Period4/15/204/17/20

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

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