Detecting Malicious Facebook Applications

Detecting Malicious Facebook Applications

Dr.V.Sucharita¹, P. Madhavi²,Sk.Sadhik Basha³, N.Rajasekhar⁴, P.Rajesh Reddy⁵,K.Venkateswarlu⁶

^{1Professor ,Department of Computer Science & Engineering, Narayana Engineering College, Gudur}

^{2Assit.Professor ,Department of Computer Science & Engineering, Narayana Engineering College, Gudur.}

^{3 Student ,Department of Computer Science & Engineering, Narayana Engineering College, Gudur.}

^{4Student ,Department of Computer Science & Engineering, Narayana Engineering College, Gudur.}

^{5 Student ,Department of Computer Science & Engineering, Narayana Engineering College, Gudur}

^{6Student ,Department of Computer Science & Engineering, Narayana Engineering College, Gudur.}

---------------------------------------------------------------------***---------------------------------------------------------------------

Abstract - With daily installs, third-party Apps may be a very important cause for the recognition and attractiveness of Facebook or any on-line social media. Sadly, cyber criminals get return to appreciate the potential of victimisation apps for spreading spam and malware. we have a tendency to notice that a minimum of thirteen of Facebook apps within the dataset ar sometimes malevolent. but with their findings , many problems like fake profiles, malicious applications have put together grown There are not any potential solutions to those issues. throughout this project, we have a tendency to tend to return up with a framework that automatic detection of malicious applications is possible and is economical. Suppose there is a Facebook application, can the Facebook user verify that the app is malicious or not. actually the Facebook user cannot establish that so The key contribution is in developing the primary tool dedicated to detection deceitful apps on Facebook is FRAppE-Rigorous Facebook's Application authority. we have a tendency to tend to leverage information nonheritable from the posting behaviour of Facebook applications seen by uncountable Facebook users to develop FRAppE. initial we have a tendency to establish a collection of options that facilitate United States to research malicious from benign ones. Second, investing these identifying options ,where we have a tendency to show that FRAppE will discover malicious apps with ninety five.9% accuracy. Finally, we have a tendency to explore the ecosystems of malicious Facebook apps and establish mechanisms that these apps use to unfold.

Key Words:apps, malicious, on-line social networks.