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The thesis mainly focuses on applying fuzzy and rough set theory to the mobile adver-tisement fraud detection. We first present an application of fuzzy set theory to implement mobile advertisement anti-fraud systems. One of the main problems of mobile anti-fraud is the lack of evidence to prove a user to be a fraudster. In this thesis, we implement an application of fuzzy set theory to demonstrate how to detect cheaters. The advantage of this method is such that the hardship in detecting fraudsters in small data samples can be avoided. We achieve this by giving each user a suspicious degree showing how likely the user is cheating and decide whether a group of users (like all users of a certain APP) together could be fraudsters according to the average suspicious degree. This makes the process more accurate as the data of a single user is too small to be predictable. We also develop another method with the application of rough set theory. The advantage of the second anti-fraud method pr

Fuzzy-set-theory
Ough-set-theory
Dvertisement-fraud-detection