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Anomaly Recognition in Online Social Networks
Ashish Rawat,Gunjan Gugnani,Minakshi Shastri,Pardeep Kumar 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.7
The popularity of social networking sites has increased throughout the decade and everything that gains immense popularity with great human involvement also brings many challenges and issues along with it. Similarly the excessive use of online social networking causes a great increase in anomalies. In social networking the anomalies are like fake account, account hack, identity theft, spams and many other illegitimate activities. It is thus necessary to detect such anomalous and suspicious behavior of any user at these social platforms, as they could have an adverse impact on users, especially on teenagers. In this paper, we propose various methodologies for early detection of suspicious and anomalous activities. We have done the analysis of various parameters of social networking and its graph like indegree, outdegree, active time of a node (user) and its behavior.