An assessment and methodology for fraud detection in online social network

Abstract

Online Social Network provides a simple and easier way to connect with our friends and relatives to share daily activities and event of our day to day life. Most of us cannot live without social network. But just like other online activity, even social networks are having lot of security threats to its users. Most of Research on Social Network reveals that Social Network are the primary sources for getting confidential information of the victim so that they can do numerous fraudulent activities like cyber bullying, money laundering, spreading fake or false messages to create panic situation in public or to fool other user. They already have set their target on social networking website to do their fraudulent activities. Fraudsters are always trying to find any loopholes in the existing system so that they can get access to the system to launch various social engineering attack and scam activities. The security and privacy on these networks has been increasing as the amount of personal information posted by millions of users in their profile is made public. A social networking site allows millions of users to communicate online and large amount of information has been posted daily. So in every few seconds a large amount of data has been generated around the world. This necessitates the adaptation of new methodology to provide security of online data. Social network users are not aware of the various security threats and the associated risks exist in these networks. This paper presents an assessment of classification different social network and different attacks present on those social networks and methodology has been proposed which help the online users to be safe from numerous fraudulent and malicious activities on the web.