CORGI: An interactive framework for Customizable and Robust Location Obfuscation

Primal Pappachan; Vishnu Sharma Hunsur Manjunath; Chenxi Qiu; Anna Squicciarini; Hailey Onweller

doi:10.1109/ICDE55515.2023.00294

CORGI: An interactive framework for Customizable and Robust Location Obfuscation

Primal Pappachan, Vishnu Sharma Hunsur Manjunath, Chenxi Qiu, Anna Squicciarini, Hailey Onweller

College of Information Sciences and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

Customizing the location obfuscation functions generated by existing systems can result in weakening the privacy guarantees offered by these functions as they are not robust against such updates. In this demo, we present a new framework called, CORGI, i.e., CustOmizable Robust Geo Indistinguishability. The demonstration platform is a web application which is built on top on a real world dataset (Gowalla). The user-friendly interface of the demo allows participants to easily specify their customization preferences and generate a customizable and robust location obfuscation function. They can also examine the trade-offs among privacy, utility, and customization; visualized on a map for comparison between CORGI and a state of the art baseline.

Original language	English (US)
Title of host publication	Proceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023
Publisher	IEEE Computer Society
Pages	3667-3670
Number of pages	4
ISBN (Electronic)	9798350322279
DOIs	https://doi.org/10.1109/ICDE55515.2023.00294
State	Published - 2023
Event	39th IEEE International Conference on Data Engineering, ICDE 2023 - Anaheim, United States Duration: Apr 3 2023 → Apr 7 2023

Publication series

Name	Proceedings - International Conference on Data Engineering
Volume	2023-April
ISSN (Print)	1084-4627

Conference

Conference	39th IEEE International Conference on Data Engineering, ICDE 2023
Country/Territory	United States
City	Anaheim
Period	4/3/23 → 4/7/23

All Science Journal Classification (ASJC) codes

Software
Signal Processing
Information Systems

Access to Document

10.1109/ICDE55515.2023.00294

Cite this

Pappachan, P., Hunsur Manjunath, V. S., Qiu, C., Squicciarini, A., & Onweller, H. (2023). CORGI: An interactive framework for Customizable and Robust Location Obfuscation. In Proceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023 (pp. 3667-3670). (Proceedings - International Conference on Data Engineering; Vol. 2023-April). IEEE Computer Society. https://doi.org/10.1109/ICDE55515.2023.00294

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abstract = "Customizing the location obfuscation functions generated by existing systems can result in weakening the privacy guarantees offered by these functions as they are not robust against such updates. In this demo, we present a new framework called, CORGI, i.e., CustOmizable Robust Geo Indistinguishability. The demonstration platform is a web application which is built on top on a real world dataset (Gowalla). The user-friendly interface of the demo allows participants to easily specify their customization preferences and generate a customizable and robust location obfuscation function. They can also examine the trade-offs among privacy, utility, and customization; visualized on a map for comparison between CORGI and a state of the art baseline.",

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Pappachan, P, Hunsur Manjunath, VS, Qiu, C, Squicciarini, A & Onweller, H 2023, CORGI: An interactive framework for Customizable and Robust Location Obfuscation. in Proceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023. Proceedings - International Conference on Data Engineering, vol. 2023-April, IEEE Computer Society, pp. 3667-3670, 39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, United States, 4/3/23. https://doi.org/10.1109/ICDE55515.2023.00294

CORGI: An interactive framework for Customizable and Robust Location Obfuscation. / Pappachan, Primal; Hunsur Manjunath, Vishnu Sharma; Qiu, Chenxi et al.
Proceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023. IEEE Computer Society, 2023. p. 3667-3670 (Proceedings - International Conference on Data Engineering; Vol. 2023-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Pappachan P, Hunsur Manjunath VS, Qiu C, Squicciarini A, Onweller H. CORGI: An interactive framework for Customizable and Robust Location Obfuscation. In Proceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023. IEEE Computer Society. 2023. p. 3667-3670. (Proceedings - International Conference on Data Engineering). doi: 10.1109/ICDE55515.2023.00294

CORGI: An interactive framework for Customizable and Robust Location Obfuscation

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