Identifying Spam in Mobile Ad Networks using Latent Class Model

  IJPTT-book-cover
 
International Journal of P2P Network Trends and Technology (IJPTT)          
 
© 2017 by IJPTT Journal
Volume - 7 Issue - 1
Year of Publication : 2017
Authors : M.Sree Vani

MLA

M.Sree Vani "Identifying Spam in Mobile Ad Networks using Latent Class Model". International Journal of P2P Network Trends and Technology (IJPTT), V7(1):22-27 Jan - Feb 2017, ISSN:2249-2615, www.ijpttjournal.org, Published by Seventh Sense Research Group.

Abstract

Smart phone Apps plays a vital role to attract mobile-Advertising. Popular apps can generate millions of dollars in profit and collect valuable personal user information. spam, i.e., fraudulent or invalid tap or click on online ads, where the user has no actual interest in the advertiser’s site, results in advertising revenue being misappropriated by spammers. It requires a user touch or click on control ads came from Smartphone-game Apps. It all need the user to tap the screen close to where the ad is displayed .While ad networks take active measures to block click-spam today, but not in mobile advertising. The presence of spam in mobile advertising is largely unknown. In this paper, we take the first systematic look at spam in mobile advertising. We propose a methodology to identify spam Apps in Smartphone-game Apps. We validate our methodology using data from major ad networks. Our findings highlight the severity of the spam in mobile advertising.

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Keywords
Spam, mobile apps, click spam