Automatic Detection of Cyber Security Related Accounts on Online Social Networks: Twitter as an example

Aslan, Ça?r? B. and Sa?lam, Rahime Belen and Li, Shujun (2018) Automatic Detection of Cyber Security Related Accounts on Online Social Networks: Twitter as an example. In: Proceedings of 9th International Conference on Social Media & Society. ACM ISBN 978-1-4503-6334-1. (doi:https://doi.org/10.1145/3217804.3217919) (Full text available)

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Abstract

Recent studies have revealed that cyber criminals tend to exchange knowledge about cyber attacks in online social networks (OSNs). Cyber security experts are another set of information providers on OSNs who frequently share information about cyber security incidents and their personal opinions and analyses. Therefore, in order to improve our knowledge about evolving cyber attacks and the underlying human behavior for different purposes (e.g., crime investigation, understanding career development and business models of cyber criminals and cyber security professionals, prediction and prevention of impeding cyber attacks), it will be very useful to detect cyber security related accounts on OSNs automatically, and monitor their activities. This paper reports our preliminary work on automatic detection of cyber security related accounts on OSNs using Twitter as an example, which may allow us to discover unknown cyber security experts and cyber criminals for monitoring purposes. Three machine learning based classification algorithms were applied and compared: decision trees, random forests, and SVM (support vector machines). Experimental results showed that both decision trees and random forests had performed well with an overall accuracy over 95%, and when random forests were used with behavioral features the accuracy had reached as high as 97.877%.

Item Type: Conference or workshop item (Proceeding)
Uncontrolled keywords: cyber, security, crime, criminals, experts, cybersecurity, cybercrime, cybercriminals, social media, machine learning, classification
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunications > TK5105 Data transmission systems > TK5105.5 Computer networks > TK5105.875.I57 Internet
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunications > TK5105.888 World Wide Web (technology of)
Divisions: Faculties > University wide - Teaching/Research Groups > Centre for Cyber Security Research
Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Security Group
Depositing User: Shujun Li
Date Deposited: 27 Apr 2018 09:40 UTC
Last Modified: 03 Sep 2018 11:20 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/66861 (The current URI for this page, for reference purposes)
Li, Shujun: https://orcid.org/0000-0001-5628-7328
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