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MadDroid: Characterizing and Detecting Devious Ad Contents for Android Apps
Liu, Tianming; Wang, Haoyu; Li, Li et al.
2020In Proceedings of The Web Conference 2020
Peer reviewed
 

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Keywords :
ad fraud; mobile advertising; Android app; malware
Abstract :
[en] Advertisement drives the economy of the mobile app ecosystem. As a key component in the mobile ad business model, mobile ad content has been overlooked by the research community, which poses a number of threats, e.g., propagating malware and undesirable contents. To understand the practice of these devious ad behaviors, we perform a large-scale study on the app contents harvested through automated app testing. In this work, we first provide a comprehensive categorization of devious ad contents, including five kinds of behaviors belonging to two categories: ad loading content and ad clicking content. Then, we propose MadDroid, a framework for automated detection of devious ad contents. MadDroid leverages an automated app testing framework with a sophisticated ad view exploration strategy for effectively collecting ad-related network traffic and subsequently extracting ad contents. We then integrate dedicated approaches into the framework to identify devious ad contents. We have applied MadDroid to 40,000 Android apps and found that roughly 6% of apps deliver devious ad contents, e.g., distributing malicious apps that cannot be downloaded via traditional app markets. Experiment results indicate that devious ad contents are prevalent, suggesting that our community should invest more effort into the detection and mitigation of devious ads towards building a trustworthy mobile advertising ecosystem.
Disciplines :
Computer science
Author, co-author :
Liu, Tianming;  Beijing University of Posts and Telecommunications
Wang, Haoyu;  Beijing University of Posts and Telecommunications
Li, Li;  Monash University
Luo, Xiapu;  The Hong Kong Polytechnic University
Dong, Feng;  Beijing University of Posts and Telecommunications
Guo, Yao;  Peking University
Wang, Liu;  Beijing University of Posts and Telecommunications
Bissyande, Tegawendé François D Assise  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX
Klein, Jacques ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX
External co-authors :
yes
Language :
English
Title :
MadDroid: Characterizing and Detecting Devious Ad Contents for Android Apps
Publication date :
April 2020
Event name :
Proceedings of The Web Conference 2020 (WWW)
Event place :
Taipei, Taiwan
Event date :
April 2020
Audience :
International
Main work title :
Proceedings of The Web Conference 2020
Publisher :
Association for Computing Machinery, New York, NY, USA, Unknown/unspecified
ISBN/EAN :
9781450370233
Collection name :
WWW '20
Pages :
1715–1726
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust
FnR Project :
FNR11693861 - Characterization Of Malicious Code In Mobile Apps: Towards Accurate And Explainable Malware Detection, 2017 (01/06/2018-31/12/2021) - Jacques Klein
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