A method for recognize malignant Facebook application
Kiran Bhise, R. S. Shishupal · 2016
One of the important factors for popularity and addiction of Facebook is due to the daily installments and use of third party apps. The new way of cybercrime is introduced by hackers in online social networks (OSNs). Hackers identified various ideas to damage the computer systems and methods to forward spam messages for advertisement purpose in illegal way. As popularity of third-party apps platform and deploying malicious applications increases so hackers have started taking advantages. Online social media is considered as a rich source of information as it provides the good quality content; however consumption of poor quality content can degrade user experience, and have unsuitable impact in the real world. In this paper we proposed system which develop tool that can predict malicious application with better results as compare to existing system. Proposed system implements the classification technique. This technique is used for identifying malicious app. System added parameters like number of user rating and user review to generate better results. That is user rating and Description Content check-up. Every app has few reviews as a feedback from user side, and we consider user mention all related to that app which is as per its experience. We consider all that reviews for checking app is malicious or benign. Existing system says that malicious app doesn't give any description but what about such malicious app which gives description and such benign app which doesn't give description…?? Its completely opposite of accuracy result. So in this paper we consider these two points as new feature of FRAppE for improving result accuracy. By including these parameters the proposed framework produces better result prediction.