Ranking fraud within the mobile App market refers to deceitful or deceptive activities that have a purpose of bumping up the Apps within the quality list. Indeed, it becomes a lot of and a lot of frequent for App developers to use shady means that, like inflating their Apps’ sales or posting phony App ratings, to commit ranking fraud. Whereas the importance of preventing ranking fraud has been well known, there's restricted understanding and analysis during this space. to the current finish, during this paper, we offer a holistic read of ranking fraud and propose a ranking fraud detection system for mobile Apps. Specifically, we have a tendency to initial propose to accurately find the ranking fraud by mining the active periods, specifically leading sessions, of mobile Apps. Such leading sessions are often leveraged for sleuthing the native anomaly rather than international anomaly of App rankings. what is more, we have a tendency to investigate 3 kinds of evidences, i.e., ranking primarily based evidences, rating based evidences and review based evidences, by modeling Apps’ ranking, rating and review behaviors through applied math hypotheses tests.