• Darshana Chaudhari
• sayali revade
• Yogita Sonje
• Yogita Jagtap
• Jyoti Deshmukh

A social behavioral profile accurately reflects a user’s OSN activity patterns. People access OSNs using both traditional desktop PCs and new emerging mobile devices. With more than one billion users worldwide, OSNs are a new venue of innovation with many challenging research problems. In this paper, we study the social behaviors of OSN users, i.e., their usage of OSN services, and the application of which in detecting the compromised accounts. We capture user behavior with the following metrics: user connectivity, user activity and user reactions.we validate and characterize the user social activity on OSN.The study is based on detailed clickstream data ,the clickstream data reveals key features of the social network workloads, such as how frequently people connect to social networks and for how long, as well as the types and sequences of activities that users conduct on these sites. we pay attention to the characteristics of social behaviors we review malicious behaviors of OSN users and show the social behavioral profiles can accurately differentiate individual OSN users and detect compromised accounts.

OSNs, user behavior, data analysis,compromised accounts detection

"enhancing compromised account detection in online social networking", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.3, Issue 12, page no.91-94, December-2016, Available :http://www.jetir.org/papers/JETIR1612012.pdf

"enhancing compromised account detection in online social networking", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.3, Issue 12, page no. pp91-94, December-2016, Available at : http://www.jetir.org/papers/JETIR1612012.pdf