Analysis of Trending Topics and Text-based Channels of Information Delivery in Cybersecurity
Tingmin Wu, Wanlun Ma, Sheng Wen, Xin Xia, Cecile Paris, Surya Nepal,, Yang Xiang

TL;DR
This paper analyzes cybersecurity texts from various sources to identify trending topics and security issues, proposing a semi-automated classification method that reveals insights into the impact and dissemination of security information.
Contribution
It introduces a semi-automated classification approach for cybersecurity texts and compares security categories across sources, revealing correlations and dissemination patterns.
Findings
Cybersecurity impact correlates with monetary losses.
Security blogs have the highest popularity and impact.
Websites often lack timeliness in delivering security information.
Abstract
Computer users are generally faced with difficulties in making correct security decisions. While an increasingly fewer number of people are trying or willing to take formal security training, online sources including news, security blogs, and websites are continuously making security knowledge more accessible. Analysis of cybersecurity texts can provide insights into the trending topics and identify current security issues as well as how cyber attacks evolve over time. These in turn can support researchers and practitioners in predicting and preparing for these attacks. Comparing different sources may facilitate the learning process for normal users by persisting the security knowledge gained from different cybersecurity context. Prior studies neither systematically analysed the wide-range of digital sources nor provided any standardisation in analysing the trending topics from recent…
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Taxonomy
TopicsInformation and Cyber Security · Spam and Phishing Detection · Cybercrime and Law Enforcement Studies
MethodsLinear Discriminant Analysis
