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Reseach Article

Survey on Fraud Ranking Detection in Mobile App Store

Published on July 2016 by M. Aadil Khan, T.h. Gurav
International Conference on Internet of Things, Next Generation Networks and Cloud Computing
Foundation of Computer Science USA
ICINC2016 - Number 3
July 2016
Authors: M. Aadil Khan, T.h. Gurav
26207ed6-8457-46a7-b688-e44fa127defd

M. Aadil Khan, T.h. Gurav . Survey on Fraud Ranking Detection in Mobile App Store. International Conference on Internet of Things, Next Generation Networks and Cloud Computing. ICINC2016, 3 (July 2016), 9-12.

@article{
author = { M. Aadil Khan, T.h. Gurav },
title = { Survey on Fraud Ranking Detection in Mobile App Store },
journal = { International Conference on Internet of Things, Next Generation Networks and Cloud Computing },
issue_date = { July 2016 },
volume = { ICINC2016 },
number = { 3 },
month = { July },
year = { 2016 },
issn = 0975-8887,
pages = { 9-12 },
numpages = 4,
url = { /proceedings/icinc2016/number3/25535-4821/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Internet of Things, Next Generation Networks and Cloud Computing
%A M. Aadil Khan
%A T.h. Gurav
%T Survey on Fraud Ranking Detection in Mobile App Store
%J International Conference on Internet of Things, Next Generation Networks and Cloud Computing
%@ 0975-8887
%V ICINC2016
%N 3
%P 9-12
%D 2016
%I International Journal of Computer Applications
Abstract

From last few years, mobile technology has been received much more attention since it is most popular and basic need of today's world. Due to the popularity, mobiles are major target for malicious applications. Key challenge is to detect and remove malicious apps from mobiles. Numerous amounts of mobile apps are generated daily so ranking fraud is the one of the major aspects in front of the mobile App market. Ranking fraud refers to fraudulent or vulnerable activities. Main aim of the fraudulent is to knock the fraud mobile apps in the popularity list. Most App developer generates the ranking fraud apps by tricky means like enhancing the apps sales or by simply rating fake apps. Thus, there is need to have novel system to effectively analyze fraud apps. This paper provides a survey on various existing techniques with the novelties highlighting the need of novel technique to detect fraud mobile apps. This paper is motivated by arising need to detect fraud apps with less time. In proposed system, we add recommendation based on the modified ranking.

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Index Terms

Computer Science
Information Sciences

Keywords

Mobile Apps Ranking Fraud Detection Evidence Aggregation Historical Ranking Records Rating And Review