期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2016
卷号：5
期号：3
页码：0701-0704
出版社：Shri Pannalal Research Institute of Technolgy
摘要：The number of mobile Apps has grown at a breathtaking rate over the past few years. To stimulate the development of mobile Apps, many App stores launched daily App leaderboards, which demonstrate the chart rankings of most popular Apps. A higher rank on the leaderboard usually leads to a huge number of downloads and million dollars in revenue. As a recent trend, instead of relying on traditional marketing solutions, shady App developers resort to some fraudulent means to deliberately boost their Apps and eventually manipulate the chart rankings on an App store. This is usually implemented by using so-called "bot farms" or "human water armies" to inflate the App downloads, ratings and reviews in a very short time. In the literature, while there are some related work, such as web ranking spam detection, online review spam detection and mobile App recommendation. The problem of detecting ranking fraud for mobile Apps is still underexplored. To fill this crucial void, in this project, we propose to develop a ranking fraud detection system for mobile Apps.
