MiniChecker: Detecting Data Privacy Risk of Abusive Permission Request Behavior in Mini-Programs

The rising popularity of mini-programs deployed on super-app platforms has drawn significant attention due to their convenience. However, developers' improper handling of data permission application in mini-programs has raised concerns about non-compliance and violations. Unfortunately, existing tools lack the capability to support the construction of a universal function call graph for the mini-program and the literature lacks a comprehensive and systematic study of the abusive issues. To bridge this gap, this paper introduces an automated tool, MiniChecker, to uncover the abusive permission request behavior in mini-programs. It defines five primary categories of abusive issues, namely homepage pop-up, overlaying pop-up, bothering pop-up, repeating pop-up, and looping pop-up, based on the request behavior features. MiniChecker achieves a detection precision rate of 82.4% and a recall rate of 95.3% on our benchmark, and identifies 3,866 risky mini-programs out of 20,000 real-world mini-programs. Our analysis reveals inherent design flaws in the mini-program permission mechanism, and we have shared our findings with several mini-program platforms.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1145/3691620.3695534
Citations
2
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.70

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article

MiniChecker: Detecting Data Privacy Risk of Abusive Permission Request Behavior in Mini-Programs

W. M. Chen, Deqiang Han, Wuxia Jin, Yin Wang et al.
2 citations
Advanced Malware Detection Techniques
0.70
article

MiniChecker: Detecting Data Privacy Risk of Abusive Permission Request Behavior in Mini-Programs

W. M. Chen, Deqiang Han, Wuxia Jin, Yin Wang, Yu Zhang, Hao Zhou, Haijun Wang, Shijie Li, Ming Yu Fan, Ting Liu, Jiajia Li
article en
2 citations

Abstract

The rising popularity of mini-programs deployed on super-app platforms has drawn significant attention due to their convenience. However, developers' improper handling of data permission application in mini-programs has raised concerns about non-compliance and violations. Unfortunately, existing tools lack the capability to support the construction of a universal function call graph for the mini-program and the literature lacks a comprehensive and systematic study of the abusive issues. To bridge this gap, this paper introduces an automated tool, MiniChecker, to uncover the abusive permission request behavior in mini-programs. It defines five primary categories of abusive issues, namely homepage pop-up, overlaying pop-up, bothering pop-up, repeating pop-up, and looping pop-up, based on the request behavior features. MiniChecker achieves a detection precision rate of 82.4% and a recall rate of 95.3% on our benchmark, and identifies 3,866 risky mini-programs out of 20,000 real-world mini-programs. Our analysis reveals inherent design flaws in the mini-program permission mechanism, and we have shared our findings with several mini-program platforms.

Hong Kong Polytechnic University (HK), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China
Gender equality
Openalex Percentile: Top 30%
Advanced Malware Detection Techniques
0.70
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MiniChecker: Detecting Data Privacy Risk of Abusive Permission Request Behavior in Mini-Programs — W. M. Chen, Deqiang Han, et al. · (2024) | TGRS Research Map | TGRS