Vulcan
| Autor: | Kefan Xu, Heng Zhang, Edgardo Barsallo Yi, Amiya K. Maji, Saurabh Bagchi |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Wearable computer 020207 software engineering Crash 02 engineering and technology Fuzz testing Computer security computer.software_genre Android Wear 020204 information systems 0202 electrical engineering electronic engineering information engineering State (computer science) computer Reliability (statistics) Reboot |
| Zdroj: | MobiSys |
| DOI: | 10.1145/3386901.3388916 |
| Popis: | As we look to use Wear OS (formerly known as Android Wear) devices for fitness and health monitoring, it is important to evaluate the reliability of its ecosystem. The goal of this paper is to understand the reliability weak spots in Wear OS ecosystem. We develop a state-aware fuzzing tool, Vulcan, without any elevated privileges, to uncover these weak spots by fuzzing Wear OS apps. We evaluate the outcomes due to these weak spots by fuzzing 100 popular apps downloaded from Google Play Store. The outcomes include causing specific apps to crash, causing the running app to become unresponsive, and causing the device to reboot. We finally propose a proof-of-concept mitigation solution to address the system reboot issue. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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