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Understanding iOS-based Crowdturfing Through Hidden UI Analysis

Authors
Lee, YeonjoonWang, XueqiangLee, KwangwukLiao, XiaojingWang, XiaofengLi, TongxinMi, Xianghang
Issue Date
Aug-2019
Publisher
USENIX
Citation
USENIX Security Symposium, pp.765 - 781
Indexed
OTHER
Journal Title
USENIX Security Symposium
Start Page
765
End Page
781
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/2393
Abstract
A new type of malicious crowdsourcing (a.k.a., crowdturfing) clients, mobile apps with hidden crowdturfing user interface (UI), is increasingly being utilized by miscreants to coordinate crowdturfing workers and publish mobile-based crowdturfing tasks (e.g., app ranking manipulation) even on the strictly controlled Apple App Store. These apps hide their crowdturfing content behind innocent-looking UIs to bypass app vetting and infiltrate the app store. To the best of our knowledge, little has been done so far to understand this new abusive service, in terms of its scope, impact and techniques, not to mention any effort to identify such stealthy crowdturfing apps on a large scale, particularly on the Apple platform. In this paper, we report the first measurement study on iOS apps with hidden crowdturfing UIs. Our findings bring to light the mobile-based crowdturfing ecosystem (e.g., app promotion for worker recruitment, campaign identification) and the underground developer’s tricks (e.g., scheme, logic bomb) for evading app vetting.
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ERICA 소프트웨어융합대학 (ERICA 컴퓨터학부)
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