An Adversarially Robust Data Market for Spatial, Crowd-sourced Data

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00387102" target="_blank" >RIV/68407700:21230/25:00387102 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1145/3703464" target="_blank" >https://doi.org/10.1145/3703464</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3703464" target="_blank" >10.1145/3703464</a>

Result language
angličtina
Original language name
An Adversarially Robust Data Market for Spatial, Crowd-sourced Data
Original language description
We describe an architecture for a decentralised data market for applications in which agents are incentivised to collaborate to crowd-source their data. The architecture is designed to reward data that furthers the market's collective goal, and distributes reward fairly to all those that contribute with their data. We show that the architecture is resilient to Sybil, wormhole and data poisoning attacks. In order to evaluate the resilience of the architecture, we characterise its breakdown points for various adversarial threat models in an automotive use case.
Czech name
—
Czech description
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Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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