Proceedings of the 9th International Conference on Social Media and Society 2018
DOI: 10.1145/3217804.3217919
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Automatic Detection of Cyber Security Related Accounts on Online Social Networks

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 diferent purposes (e.g., crime investigation, understanding career development and business mo… Show more

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Cited by 26 publications
(19 citation statements)
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“…Surprisingly, although a lot of work has been done on using OSN data to analyze activities and behaviors of hackers, cyber criminals and other types of cyber attackers [8]- [15], [29], [30], there has been very limited research on using OSN data to study defacement attacks and defacers. The only work we are aware of was done by Maimon et al in 2017 [31].…”
Section: Romagna Et Al's Work Depended On Tags Onmentioning
confidence: 99%
“…Surprisingly, although a lot of work has been done on using OSN data to analyze activities and behaviors of hackers, cyber criminals and other types of cyber attackers [8]- [15], [29], [30], there has been very limited research on using OSN data to study defacement attacks and defacers. The only work we are aware of was done by Maimon et al in 2017 [31].…”
Section: Romagna Et Al's Work Depended On Tags Onmentioning
confidence: 99%
“…The process of real-time cybersecurity account detection on Twitter is based on three different feature sets and three different methods of machine learning, which are decision trees, random forests, and SVM [10]. The DeepScan model splits the activity data of each user into many continuous-time intervals.…”
Section: Machine Learning Approachmentioning
confidence: 99%
“…The spotlight is a 5 x 5 pixel space. In the wake of the sparkling super-left territory, the spotlight shifts with the final goal of slipping through all the information picture / content territories [34]. This spotlight is known as a platform or part of CNN [35].…”
Section: Figure 3 Cnn Pixel Processing Architecturementioning
confidence: 99%