Date of Publication :22nd February 2018

Abstract: Compromised accounts are of a severe risk to the social network users. People nowadays are mostly dependent on Online Social Networks. While some persistent spams feat the relationship between the users by spreading spams. Therefore time to time detection of the compromised accounts is a necessity. In this paper, we will study different social user behaviour and detect the compromised accounts and spam users. Spam behaviour in social networks has a wide range of illegal activities. Such activities need to be evaluated and effect of spam users needs to be reduced. To reduce such effects, we require proper detection strategy. We validate the effectiveness of this behaviour by collecting the clickstream data on a social network website. Social behaviour reflects the user's behaviour online. While a legitimate user coordinates its social behaviour carefully, it is hard for the fake users to pretend to be affected. Different studies are performed in spam behaviour analysis and define a structure for spam account detection.

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