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A Large-Scale Study on the Prevalence and Usage of TEE-based Features on Android

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arxiv 2311.10511 v1 pith:E6GORDHJ submitted 2023-11-17 cs.CR

classification cs.CR
keywords analysisandroidfeatureslarge-scaleappssecuritytechnologytee-based
verification ladder T0 review T1 audit T2 compute T3 formal

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In the realm of mobile security, where OS-based protections have proven insufficient against robust attackers, Trusted Execution Environments (TEEs) have emerged as a hardware-based security technology. Despite the industry's persistence in advancing TEE technology, the impact on end users and developers remains largely unexplored. This study addresses this gap by conducting a large-scale analysis of TEE utilization in Android applications, focusing on the key areas of cryptography, digital rights management, biometric authentication, and secure dialogs. To facilitate our extensive analysis, we introduce Mobsec Analytika, a framework tailored for large-scale app examinations, which we make available to the research community. Through the analysis of 170,550 popular Android apps, our analysis illuminates the implementation of TEE-related features and their contextual usage. Our findings reveal that TEE features are predominantly utilized indirectly through third-party libraries, with only 6.7% of apps directly invoking the APIs. Moreover, the study reveals the underutilization of the recent TEE-based UI feature Protected Confirmation.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. KeyDroid: A Large-Scale Analysis of Secure Key Storage in Android Apps

    cs.CR 2025-07 conditional novelty 8.0 of 10

    Most Android apps that collect sensitive data still rely on software key storage, and the first large-scale benchmarks show secure-element key operations are far too slow for anything but small payloads.

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