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PROJECT TITLE :

Detecting Malicious Facebook Applications

ABSTRACT:

With twenty million installs on a daily basis , third-party apps are a serious reason for the popularity and addictiveness of Facebook. Unfortunately, hackers have realized the potential of using apps for spreading malware and spam. The problem is already significant, as we tend to notice that a minimum of thirteenpercent of apps in our dataset are malicious. Therefore so much, the research community has focused on detecting malicious posts and campaigns. During this paper, we ask the question: Given a Facebook application, can we have a tendency to verify if it's malicious? Our key contribution is in developing FRAppE—Facebook’s Rigorous Application Evaluator—arguably the first tool centered on detecting malicious apps on Facebook. To develop FRAppE, we use data gathered by observing the posting behavior of 111K Facebook apps seen across a pair of.two million users on Facebook. Initial, we have a tendency to establish a group of features that help us distinguish malicious apps from benign ones. For example, we have a tendency to find that malicious apps usually share names with alternative apps, and that they sometimes request fewer permissions than benign apps. Second, leveraging these distinguishing options, we have a tendency to show that FRAppE will detect malicious apps with 99.fivepercent accuracy, with no false positives and a high true positive rate (95.9p.c). Finally, we tend to explore the ecosystem of malicious Facebook apps and establish mechanisms that these apps use to propagate. Interestingly, we have a tendency to realize that many apps collude and support every other; in our dataset, we notice 1584 apps enabling the viral propagation of 3723 different apps through their posts. Future, we see FRAppE as a step toward making an freelance watchdog for app assessment and ranking, thus as to warn Facebook users before putting in apps.


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