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Jason Matthew Brauer

dblp:359/3426 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0006-3174-2623ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Cyber-physical and IoT security · 100%
Software engineering, system software, and programming languages
1 paper
Software testing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cyber-physical and IoT security
UAV security
0.812024
HIFuzz: Human Interaction Fuzzing for Small Unmanned Aerial Vehicles · CHI 2024
Software testing › system testing
cyber-physical system testing
0.212024
HIFuzz: Human Interaction Fuzzing for Small Unmanned Aerial Vehicles · CHI 2024
Software testing
fuzzing
0.212024
HIFuzz: Human Interaction Fuzzing for Small Unmanned Aerial Vehicles · CHI 2024

Methods — techniques the papers use, named apart from their topics

simulation · 1.5fuzz testing · 1.5
YearPublicationVenuePosition
2024 HIFuzz: Human Interaction Fuzzing for Small Unmanned Aerial Vehicles
abstract
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.
Theodore Chambers, Michael Vierhauser, Ankit Agrawal 0002, Michael Murphy, Jason Matthew Brauer, Salil Purandare, Myra B. Cohen, Jane Cleland-Huang
CHI5