Understanding iOS-based Crowdturfing Through Hidden UI Analysis


Yeonjoon Lee, Xueqiang Wang, Kwangwuk Lee, Xiaojing Liao, and XiaoFeng Wang, Indiana University; Tongxin Li, Peking University; Xianghang Mi, Indiana University


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.

@inproceedings {236272,
title = {Understanding iOS-based Crowdturfing Through Hidden {UI} Analysis},
booktitle = {28th {USENIX} Security Symposium ({USENIX} Security 19)},
year = {2019},
address = {Santa Clara, CA},
url = {https://www.usenix.org/conference/usenixsecurity19/presentation/lee},
publisher = {{USENIX} Association},