Funding – Platial Analysis Lab

New NSERC funding for homomorphic encryption research

May 30, 2023

The lab was recently awarded funding from NSERC to study homomorphic encryption techniques for analyzing, and preserving the privacy of, human mobility data…

New “Idea to Innovation” grant from NSERC

February 2, 2023

The lab was recently awarded a grant from the Natural Sciences and Engineering Research Council of Canada’s (NSERC) Idea to Innovation program…

Investigating ship speed on the St. Lawrence

March 28, 2022

The lab was recently awarded funding from the Quebec Maritime Network to help study the impact of ship speed on St. Lawrence river communities…

Seeking applications for fully funded Master’s degree

March 25, 2022

There is still time to apply! The Lab has fully funded positions for Master’s students interested in working with community groups near the Saint Lawrence river…

Two lab members awarded research scholarships

May 7, 2021

We are happy to announce that two Platial Analysis Lab team members have been awarded scholarships to support their graduate research…

New CIRA funding for Location Privacy Educational Platform

June 25, 2020

We are happy to share that our research proposal to build a Location Privacy Educational Platform was selected for funding by the Canadian Internet Registration Authority…

Lab receives new funding for location privacy research

May 28, 2020

The lab is pleased to announce that we were recently awarded a grant from the Quebec government to support our continued research on location privacy…

Brunila, Mikael; LaViolette, Jack; CH-Wang, Sky; Verma, Priyanka; Féré, Clara; McKenzie, Grant

Toward a Critical Toponymy Framework for Named Entity Recognition: A Case Study of Airbnb in New York City Proceedings Article Forthcoming

In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP2023), Forthcoming.

Abstract | Links | BibTeX

McKenzie, Grant; Zhang, Hongyu

Platial k-anonymity: Improving location anonymity through temporal popularity signatures Best Paper Proceedings Article

In: Proceedings of the 12th International Conference on Geographic Information Science, Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, 2023, ISSN: 1868-8969.

Abstract | Links | BibTeX

@inproceedings{McKenzie2023b,

title = {Platial k-anonymity: Improving location anonymity through temporal popularity signatures},

author = {Grant McKenzie and Hongyu Zhang },

url = {https://drops.dagstuhl.de/opus/volltexte/2023/18904/},

issn = {1868-8969},

year  = {2023},

date = {2023-08-31},

urldate = {2023-08-31},

booktitle = {Proceedings of the 12th International Conference on Geographic Information Science},

volume = {277},

publisher = {Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik},

series = {Leibniz International Proceedings in Informatics (LIPIcs)},

abstract = {While it is increasingly necessary in today's digital society, sharing personal location information comes at a cost.  Sharing one's precise place of interest, e.g., Compass Coffee, enables a range of location-based services, but substantially reduces the individual's privacy.  Methods have been developed to obfuscate and anonymize location data while still maintaining a degree of utility.  One such approach, spatial k-anonymity, aims to ensure an individual's level of anonymity by reporting their location as a set of k potential locations rather than their actual location alone.  Larger values of k increase spatial anonymity while decreasing the utility of the location information.  Typical examples of spatial k-anonymized datasets present elements as simple geographic points with no attributes or contextual information.  In this work, we demonstrate that the addition of publicly available contextual data can significantly reduce the anonymity of a k-anonymized dataset.  Through the analysis of place type temporal visitation patterns, hours of operation, and popularity values, one's anonymity can decreased by more than 50 percent.  We propose a platial k-anonymity approach that leverages a combination of temporal popularity signatures and report the amount that k must increase in order to maintain a certain level of anonymity. Finally, a method for reporting platial k-anonymous regions is presented and the implications of our methods are discussed.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

Qiang, Dan; McKenzie, Grant

Mobility Vitality: Assessing Neighborhood Similarity Through Transportation Patterns In New York City Proceedings Article

In: Proceedings of the 12th International Conference on Geographic Information Science, Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, 2023.

Abstract | BibTeX

Brunila, Mikael; Verma, Priyanka; McKenzie, Grant

When Everything Is "Nearby": How Airbnb Listings in New York City Exaggerate Proximity Proceedings Article

In: Proceedings of the 12th International Conference on Geographic Information Science, Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, 2023.

Abstract | Links | BibTeX