Recognize Fraud Accounts on Social Platform Using SVM and Neural Networks

Abstract

The present generation, online social networks (OSNs) have become increasingly popular, people’s social lives has become more associated with these sites. They use OSNs to keep in touch with each other’s, share news, organize events, and even run their own e-business. The rabid growth of OSNs and the massive amount of personal data of its subscribers have attracted attackers, and imposters to steal personal data, share false news, and spread malicious activities. On the other hand researchers have started to investigate efficient techniques to detect abnormal activities and fake accounts relying on accounts features, and classification algorithms. However, some of the account’s exploited features have negative contribution in the final results or have no impact, also using standalone classification algorithms does not always reach satisfied results. In this paper, a new algorithm, SVIn M-NN, is proposed to provide efficient detection for fake Instagram accounts, four feature selection and dimension reduction techniques were applied.