Dissecting Mobile Offerwall Advertisements: An Explorative Study

Xu, Xu; Hu, Yangyu; Guo, Qian; Ren, He; Li, Li; Xu, Guizhi; Han, Zhihui; Wang, Haoyu

doi:10.1109/qrs51102.2020.00072

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…They observed that although the overall ecosystem shows promising progress, there still exists a considerable number of unsolved security issues. Besides, some studies were focused on app developers [56,59,62], app market maintenance behaviors [54,57,58], app clone detection [35,36,52], third-party libraries [25,40,50,64,65], security [24,31,32,38,39,49,55,68,69] and privacy issues [37,44,45,50,51,63] of the ecosystem, based on app binary analysis, UI analysis, app traffic analysis, and app metadata analysis, etc. This paper, investigates the mobile app ecosystem from a novel perspective, to understanding how the dynamic trajectory of the COVID-19 pandemic shapes mobile smartphone users' experiences.…”

Section: Related Work On the Mobile App Ecosystemmentioning

confidence: 99%

A Tale of Two Countries: A Longitudinal Cross-Country Study of Mobile Users' Reactions to the COVID-19 Pandemic Through the Lens of App Popularity

Wang,

Wang

et al. 2021

Preprint

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The ongoing COVID-19 pandemic has profoundly impacted people's life around the world, including how they interact with mobile technologies. In this paper, we seek to develop an understanding of how the dynamic trajectory of a pandemic shapes mobile phone users' experiences. Through the lens of app popularity, we approach this goal from a cross-country perspective. We compile a dataset consisting of six-month daily snapshots of the most popular apps in the iOS App Store in China and the US, where the pandemic has exhibited distinct trajectories. Using this longitudinal dataset, our analysis provides detailed patterns of app ranking during the pandemic at both category and individual app levels. We reveal that app categories' rankings are correlated with the pandemic, contingent upon country-specific development trajectories. Our work offers rich insights into how the COVID-19, a typical global public health crisis, has influence people's day-to-day interaction with the Internet and mobile technologies.

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Section: Related Work On the Mobile App Ecosystemmentioning

confidence: 99%

A Tale of Two Countries: A Longitudinal Cross-Country Study of Mobile Users' Reactions to the COVID-19 Pandemic Through the Lens of App Popularity

Wang,

Wang

et al. 2021

Preprint

Self Cite

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“…Those adware/malware often not work along but collaborate with many third parties over the internet. Some of the representative malicious behaviors include leading users to malicious websites through devious advertisements [22,23,46,71], distributing malicious apps in the mobile network through drive-by downloads [19], leaking users' sensitive data to web servers through HTTP connections [28,37,47,65], etc.…”

Section: Introductionmentioning

confidence: 99%

Demystifying Hidden Sensitive Operations in Android Apps

Sun

Chen

et al. 2023

ACM Trans. Softw. Eng. Methodol.

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Security of Android devices is now paramount, given their wide adoption among consumers. As researchers develop tools for statically or dynamically detecting suspicious apps, malware writers regularly update their attack mechanisms to hide malicious behavior implementation. This poses two problems to current research techniques: static analysis approaches, given their over-approximations, can report an overwhelming number of false alarms, while dynamic approaches will miss those behaviors that are hidden through evasion techniques. We propose in this work a static approach specifically targeted at highlighting hidden sensitive operations, mainly sensitive data flows. The prototype version of HiSenDroid has been evaluated on a large-scale dataset of thousands of malware and goodware samples on which it successfully revealed anti-analysis code snippets aiming at evading detection by dynamic analysis. We further experimentally show that, with FlowDroid, some of the hidden sensitive behaviors would eventually lead to private data leaks. Those leaks would have been hard to spot either manually among the large number of false positives reported by the state of the art static analyzers, or by dynamic tools. Overall, by putting the light on hidden sensitive operations, HiSenDroid helps security analysts in validating potential sensitive data operations, which would be previously unnoticed.

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Dissecting Mobile Offerwall Advertisements: An Explorative Study

Cited by 2 publications

References 33 publications

A Tale of Two Countries: A Longitudinal Cross-Country Study of Mobile Users' Reactions to the COVID-19 Pandemic Through the Lens of App Popularity

A Tale of Two Countries: A Longitudinal Cross-Country Study of Mobile Users' Reactions to the COVID-19 Pandemic Through the Lens of App Popularity

Demystifying Hidden Sensitive Operations in Android Apps

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