Spammer detection of social networking sites using 4 novel techniques
Journal Title: International Journal of Engineering Sciences & Research Technology - Year 30, Vol 3, Issue 6
Abstract
Social Networking sites number of users are increasing day by day. Facebook is haing 2 billion users from all over the world. Twitter also having large number of users and they pay the dues if account gets hacked. Many researchers are working on to provide the securities to social networking sites. Providing security to social networking site has become a major task for researcher. Social networking sites have the personal data of users where they interact with each other. But spammers use these sites as platform to spread spam, malware and viruses. There are few techniques which are used to detect the spammers such as machine learning and honey-pot. Spammers are totally aware of these techniques, they know how to penetrate those security techniques and spread the spams. We are introducing novel technique which uses the graph generation, timed based, API based and neighbour based techniques to detect the spammers on social networking sites, which reduces the false positive rate and increases the spam detection rate.
Authors and Affiliations
Sachin H. Bankar
Keywords
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