Strangers Intrusion Detection - Detecting Spammers and Fake Proles in Social Networks Based on Topology Anomalies
Strangers Intrusion Detection - Detecting Spammers and Fake Proles in Social Networks Based on Topology Anomalies
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发表时间：
2012-12
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通讯作者：
Michael Fire;Gilad Katz;Y. Elovici
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作者：
Michael Fire;Gilad Katz;Y. Elovici
Today's social networks are plagued by numeroustypes of malicious proles which can range from so-cialbots to sexual predators. We present a novelmethod for the detection of these malicious prolesby using the social network's own topological fea-tures only. Reliance on these features alone ensuresthat the proposed method is generic enough to beapplied to a range of social networks. The algorithmhas been evaluated on several social networks andwas found to be eective in detecting various typesof malicious proles. We believe this method is avaluable step in the increasing battle against socialnetwork spammers, socialbots, and sexual predictors.
