Malicious accounts detection from online social networks: a systematic review of literature

The bourgeoning of Online Social Networks has triggered an increase in undesirable acts caused by some disruptive entities, e.g. fake accounts, bots, and cyber-extremists. Thence, detection systems for unveiling malicious accounts and mitigating their harmful behavior were taken by a storm. This paper presents a systematic review of the literature on malicious account detection and comprehensive analysis from a social network perspective. We critically explore the detection approaches to identify the unsolved problems in the domain. We scrutinized 147 articles to come out with the following findings: the targeted malicious accounts category, the list of features selected for the detection task, the social platform which offered features information, the application area that requires detection of malicious accounts, a comparison between detection methods, a comparison between available datasets, and the performance metrics used for validation. We also discuss the forthcoming challenges in terms of detection methods, annotation techniques, and validation protocols.