License: 
Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GIScience.2023.12
URN: urn:nbn:de:0030-drops-189078
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18907/
Adams, Benjamin
Confidential, Decentralized Location-Based Data Services (Short Paper)
Abstract
There are many privacy risks when location data is collected and aggregated. We introduce the notion of using confidential smart contracts for building location-based decentralized applications that are privacy preserving. We describe a spatial library for smart contracts that run on Secret Network, a blockchain network that runs smart contracts in secure enclaves running in trusted execution environments. The library supports not only basic geometric operations but also cloaking and differential privacy mechanisms applied to spatial data stored in the contract.
BibTeX - Entry
@InProceedings{adams:LIPIcs.GIScience.2023.12,
author = {Adams, Benjamin},
title = {{Confidential, Decentralized Location-Based Data Services}},
booktitle = {12th International Conference on Geographic Information Science (GIScience 2023)},
pages = {12:1--12:6},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-288-4},
ISSN = {1868-8969},
year = {2023},
volume = {277},
editor = {Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2023/18907},
URN = {urn:nbn:de:0030-drops-189078},
doi = {10.4230/LIPIcs.GIScience.2023.12},
annote = {Keywords: spatial data, privacy, smart contract, differential privacy}
}
