A survey on detection of cybersecurity threats on Twitter using deep learning

Alsodi, Omar and Zhou, Xujuan and Gururajan, Raj ORCID: https://orcid.org/0000-0002-5919-0174 and Shrestha, Anup ORCID: https://orcid.org/0000-0002-2952-0072 (2021) A survey on detection of cybersecurity threats on Twitter using deep learning. In: 8th International Conference on Behavioural and Social Computing (BESC 2021), 29 Oct - 31 Oct 2021, Doha, Qatar.


Abstract

In these times of increasing cybersecurity threats, monitoring and analysing cybersecurity events in a timely and effective way is the key to promote social media security. Twitter is one of the world's widely used social media platforms where users can share their preferences, images, opinions, and events. The Twitter platform can promptly aggregate cyber-related events and provide a source of information about cyber threats. Likewise, Deep Learning can play a critical role to help social media providers achieve a more accurate assessment of cybersecurity threats. In this paper, we have reviewed various threats and discussed deep learning techniques to detect cybersecurity threats on Twitter.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Business (18 Jan 2021 -)
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Business (18 Jan 2021 -)
Date Deposited: 02 Feb 2022 04:51
Last Modified: 21 Oct 2022 00:08
Uncontrolled Keywords: cyber security, deep learning, Twitter, cybersecurity threats, social media
Fields of Research (2008): 08 Information and Computing Sciences > 0806 Information Systems > 080602 Computer-Human Interaction
08 Information and Computing Sciences > 0806 Information Systems > 080699 Information Systems not elsewhere classified
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4604 Cybersecurity and privacy > 460499 Cybersecurity and privacy not elsewhere classified
Identification Number or DOI: https://doi.org/10.1109/BESC53957.2021.9635406
URI: http://eprints.usq.edu.au/id/eprint/44495

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