FbDetector: Malicious App Tracing Using Neural Networks

Authors

  • Jebasty Ajitha III MCA, Lord Jegannath College of Engineering & Technology
  • D.Sharmila Assistant Professor/HOD, Department of Computer Applications, Lord Jegannath College of Engineering & Technology

Keywords:

Facebook, malicious apps, API

Abstract

Facebook provides developers an API that facilitates apps integration into the Facebook user experience. Recently, hackers have started taking advantage of the popularity of this third-party apps platform and deploying malicious applications. Our key contribution is in developing FbDetector (Facebook Detector) arguably the first tool focused on detecting malicious apps on Facebook. To develop FbDetector, we use information gathered by observing the posting behavior of 111K Facebook seen across 2.2 million users on Facebook. First, we identify a set of features that help us differentiate malicious apps from benign ones. In FbDetector we are using neural network classifier for training and testing benign and malicious Facebook application.

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Published

25-03-2017

How to Cite

JebastyAjitha.S, & Dr.D.Sharmila. (2017). FbDetector: Malicious App Tracing Using Neural Networks. ERES International Journal of Computer Networks, 5(1), 23–27. Retrieved from https://eresjournals.org/journals/index.php/ijcn/article/view/28