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Vulcan: a state-aware fuzzing tool for wear OS ecosystem

Published: 15 June 2020 Publication History

Abstract

This demo abstract introduces Vulcan, a fuzz testing tool for evaluating the robustness of wearable device by injecting intra-device and inter-device communication messages. Vulcan first builds a state-model of a wearable app by offline training then steers the app to a target state for injecting mutated messages. The target state of the app typically runs a high number of concurrent processes. By testing a set of 100 popular Wear OS apps, Vulcan was able to trigger 45 unique crashes and 18 system reboots. These system reboots are triggered by a fuzzing user-level app and we present a mitigation strategy to prevent it.

References

[1]
Edgardo Barsallo, Heng Zhang, Amiya Maji, Kefan Xu, and Saurabh Bagchi. 2020. Vulcan: Lessons in Reliability of Wearables through State-Aware Fuzzing. In MobiSys.
[2]
Edgardo Barsallo Yi, Amiya K Maji, and Saurabh Bagchi. 2018. How Reliable is my Wearable: A Fuzz Testing-based Study. In DSN. 410--417.
[3]
Tianxiao Gu, Chengnian Sun, Xiaoxing Ma, Chun Cao, Chang Xu, Yuan Yao, Qirun Zhang, Jian Lu, and Zhendong Su. 2019. Practical GUI testing of Android applications via model abstraction and refinement. In ICSE. 269--280.
[4]
IDC. 2020. . Retrieved March 10, 2020 from https://www.idc.com/getdoc.jsp?containerId=prUS46122120
[5]
Renju Liu and Felix Xiaozhu Lin. 2016. Understanding the characteristics of android wear os. In Mobisys. 151--164.
[6]
Brandon Lucia and Luis Ceze. 2013. Cooperative empirical failure avoidance for multithreaded programs. ACM SIGPLAN Notices 48, 4 (2013), 39--50.
[7]
Hailong Zhang, Haowei Wu, and Atanas Rountev. 2018. Detection of energy inefficiencies in android wear watch faces. In FSE. ACM, 691--702.

Cited By

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  • (2023)Who Is Benefiting from Your Fitness Data? A Privacy Analysis of SmartwatchesSecurity Protocols XXVIII10.1007/978-3-031-43033-6_11(97-112)Online publication date: 21-Oct-2023

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cover image ACM Conferences
MobiSys '20: Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services
June 2020
496 pages
ISBN:9781450379540
DOI:10.1145/3386901
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 June 2020

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Author Tags

  1. Wear OS
  2. android
  3. fuzzer
  4. reliability
  5. wearable

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  • Demonstration

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MobiSys '20
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Overall Acceptance Rate 274 of 1,679 submissions, 16%

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Cited By

View all
  • (2023)Who Is Benefiting from Your Fitness Data? A Privacy Analysis of SmartwatchesSecurity Protocols XXVIII10.1007/978-3-031-43033-6_11(97-112)Online publication date: 21-Oct-2023

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