# A Comprehensive Analysis of Evolving Permission Usage in Android Apps: Trends, Threats, and Ecosystem Insights

arXiv: https://arxiv.org/abs/2508.02008 · HTML: https://mlsanity.com/paper/2508.02008/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 59 references that are in the map.
- First posted on arXiv 4 Aug 2025.

## Builds on (most cited first, 8 of 8)

- [Android Permissions Remystified: A Field Study on Contextual Integrity](https://mlsanity.com/paper/1504.03747/) (2015)
- [Detecting and Classifying Android Malware using Static Analysis along with Creator Information](https://mlsanity.com/paper/1903.01618/) (2019)
- [Identification of Significant Permissions for Efficient Android Malware Detection](https://mlsanity.com/paper/2103.00643/) (2021)
- [Aper: Evolution-Aware Runtime Permission Misuse Detection for Android Apps](https://mlsanity.com/paper/2201.12542/) (2022)
- [The Android Platform Security Model (2023)](https://mlsanity.com/paper/1904.05572/) (2019)
- [Towards Accurate Labeling of Android Apps for Reliable Malware Detection](https://mlsanity.com/paper/2007.00464/) (2020)
- [An Android Application Risk Evaluation Framework Based on Minimum Permission Set Identification](https://mlsanity.com/paper/2001.08399/) (2020)
- [Understanding Internet of Things Malware by Analyzing Endpoints in their Static Artifacts](https://mlsanity.com/paper/2103.14217/) (2021)

## Abstract (arXiv)

The proper use of Android app permissions is crucial to the success and security of these apps. Users must agree to permission requests when installing or running their apps. Despite official Android platform documentation on proper permission usage, there are still many cases of permission abuse. This study provides a comprehensive analysis of the Android permission landscape, highlighting trends and patterns in permission requests across various applications from the Google Play Store. By distinguishing between benign and malicious applications, we uncover developers' evolving strategies, with malicious apps increasingly requesting fewer permissions to evade detection, while benign apps request more to enhance functionality. In addition to examining permission trends across years and app features such as advertisements, in-app purchases, content ratings, and app sizes, we leverage association rule mining using the FP-Growth algorithm. This allows us to uncover frequent permission combinations across the entire dataset, specific years, and 16 app genres. The analysis reveals significant differences in permission usage patterns, providing a deeper understanding of co-occurring permissions and their implications for user privacy and app functionality. By categorizing permissions into high-level semantic groups and examining their application across distinct app categories, this study offers a structured approach to analyzing the dynamics within the Android ecosystem. The findings emphasize the importance of continuous monitoring, user education, and regulatory oversight to address permission misuse effectively.