Corpus and Deep Learning Classifier for Collection of Cyber Threat Indicators in Twitter Stream

Vahid Behzadan, Carlos Aguirre, Avishek Bose, William Hsu

Research output: Contribution to conferencePaper

8 Scopus citations

Abstract

© 2018 IEEE. This paper presents a framework for detection and classification of cyber threat indicators in the Twitter stream. Contrary to the bulk of similar proposals that rely on manually-designed heuristics and keywordbased filtering of tweets, our framework provides a data-driven approach for modeling and classification of tweets that are related to cybersecurity events. We present a cascaded Convolutional Neural Network (CNN) architecture, comprised of a binary classifier for detection of cyber-related tweets, and a multi-class model for the classification of cyber-related tweets into multiple types of cyber threats. Furthermore, we present an open-source dataset of 21000 annotated cyber-related tweets to facilitate the validation and further research in this area.
Original languageAmerican English
Pages5002-5007
Number of pages4501
DOIs
StatePublished - 22 Jan 2019
Externally publishedYes
EventProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 -
Duration: 22 Jan 2019 → …

Conference

ConferenceProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018
Period22/01/19 → …

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