HIFuzz: Human Interaction Fuzzing for Small Unmanned Aerial Vehicles

要旨

Small Unmanned Aerial Systems (sUAS) must meet rigorous safety standards when deployed in high-stress emergency response scenarios; however many reported accidents have involved humans in the loop. In this paper, we, therefore, present the HiFuzz testing framework, which uses fuzz testing to identify system vulnerabilities associated with human interactions. HiFuzz includes three distinct levels that progress from a low-cost, limited-fidelity, large-scale, no-hazard environment, using fully simulated Proxy Human Agents, via an intermediate level, where proxy humans are replaced with real humans, to a high-stakes, high-cost, real-world environment. Through applying HiFuzz to an autonomous multi-sUAS system-under-test, we show that each test level serves a unique purpose in revealing vulnerabilities and making the system more robust with respect to human mistakes. While HiFuzz is designed for testing sUAS systems, we further discuss its potential for use in other Cyber-Physical Systems.

受賞
Honorable Mention
著者
Theodore Chambers
University of Notre Dame, Notre Dame, Indiana, United States
Michael Vierhauser
University of Innsbruck, Innsbruck, Austria
Ankit Agrawal
Saint Louis University, Saint Louis, Missouri, United States
Michael Murphy
University of Notre Dame, South Bend, Zip 46637, Indiana, United States
Jason Matthew Brauer
Drone Response, Denver, Colorado, United States
Salil Purandare
Iowa State University, Ames, Iowa, United States
Myra B. Cohen
Iowa State University, Ames, Iowa, United States
Jane Cleland-Huang
University of Notre Dame, Notre Dame, Indiana, United States
論文URL

https://doi.org/10.1145/3613904.3642958

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Drone Interaction

316A
5 件の発表
2024-05-16 01:00:00
2024-05-16 02:20:00