Demo Data from EDBT 2026 / reviewers in the wild / expert
Jason Matthew Brauer
dblp:359/3426
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cyber-physical and IoT security
UAV security |
0.8 | 1 | 2024 | HIFuzz: Human Interaction Fuzzing for Small Unmanned Aerial Vehicles · CHI 2024 |
Software testing › system testing
cyber-physical system testing |
0.2 | 1 | 2024 | HIFuzz: Human Interaction Fuzzing for Small Unmanned Aerial Vehicles · CHI 2024 |
Software testing
fuzzing |
0.2 | 1 | 2024 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | HIFuzz: Human Interaction Fuzzing for Small Unmanned Aerial VehiclesabstractSmall 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 |
CHI | 5 |