Detecting Hacked Twitter Accounts by Examining Behavioural Change using Twitter Metadata

Abstract

Social media accounts are valuable for hackers for spreading phishing links, malware and spam. Furthermore, some people deliberately hack an acquaintance to damage his image. In this paper, a classification model is described for detecting these hacked Twitter accounts by examining changing features in behaviour. We look at changes in language, source, URL… (More)

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