Guileak: Tracing privacy policy claims on user input data for android applications

X Wang, X Qin, MB Hosseini, R Slavin… - Proceedings of the 40th …, 2018 - dl.acm.org
The Android mobile platform supports billions of devices across more than 190 countries
around the world. This popularity coupled with user data collection by Android apps has …

Deepintent: Deep icon-behavior learning for detecting intention-behavior discrepancy in mobile apps

S Xi, S Yang, X Xiao, Y Yao, Y Xiong, F Xu… - Proceedings of the …, 2019 - dl.acm.org
Mobile apps have been an indispensable part in our daily life. However, there exist many
potentially harmful apps that may exploit users' privacy data, eg, collecting the user's …

C2S: translating natural language comments to formal program specifications

J Zhai, Y Shi, M Pan, G Zhou, Y Liu, C Fang… - Proceedings of the 28th …, 2020 - dl.acm.org
Formal program specifications are essential for various software engineering tasks, such as
program verification, program synthesis, code debugging and software testing. However …

Android malware detection using complex-flows

F Shen, J Del Vecchio, A Mohaisen… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper proposes a new technique to detect mobile malware based on information flow
analysis. Our approach examines the structure of information flows to identify patterns of …

Iconintent: automatic identification of sensitive ui widgets based on icon classification for android apps

X Xiao, X Wang, Z Cao, H Wang… - 2019 IEEE/ACM 41st …, 2019 - ieeexplore.ieee.org
Many mobile applications (ie, apps) include UI widgets to use or collect users' sensitive data.
Thus, to identify suspicious sensitive data usage such as UI-permission mismatch, it is …

Precise android api protection mapping derivation and reasoning

Y Aafer, G Tao, J Huang, X Zhang, N Li - Proceedings of the 2018 ACM …, 2018 - dl.acm.org
The Android research community has long focused on building an Android API permission
specification, which can be leveraged by app developers to determine the optimum set of …

[PDF][PDF] Finding clues for your secrets: semantics-driven, learning-based privacy discovery in mobile apps.

Y Nan, Z Yang, X Wang, Y Zhang, D Zhu, M Yang - NDSS, 2018 - cs.uwaterloo.ca
A long-standing challenge in analyzing information leaks within mobile apps is to
automatically identify the code operating on sensitive data. With all existing solutions relying …

Android security using nlp techniques: a review

S Sen, B Can - arXiv preprint arXiv:2107.03072, 2021 - arxiv.org
Android is among the most targeted platform by attackers. While attackers are improving
their techniques, traditional solutions based on static and dynamic analysis have been also …

Do as you say: Consistency detection of data practice in program code and privacy policy in mini-app

Y Wang, M Fan, J Liu, J Tao, W Jin… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Mini-app is an emerging form of mobile application that combines web technology with
native capabilities. Its features, eg, no need to download and no installation, have made it …

Detecting information flow by mutating input data

B Mathis, V Avdiienko, EO Soremekun… - 2017 32nd IEEE …, 2017 - ieeexplore.ieee.org
Analyzing information flow is central in assessing the security of applications. However,
static and dynamic analyses of information flow are easily challenged by non-available or …