CORGI: An interactive framework for Customizable and Robust Location Obfuscation

CORGI: An interactive framework for Customizable and Robust Location Obfuscation

연구 분야: Analysis

학회: 2023 IEEE 39th International Conference on Data Engineering (ICDE)

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.