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  • PhD Defense - Kien Nguyen

    Mon, Aug 16, 2021 @ 10:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

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    Ph.D. Candidate: Kien Nguyen

    Time: August 16, 2021, 10am-12

    Title: Privacy-Aware Geo-Marketplaces

    Committee: Prof. Cyrus Shahabi (chair), Prof. Peter Kuhn, Prof. Bhaskar Krishnamachari, Dr. John Krumm

    The advance of modern mobile communication devices has enabled people to easily create, consume, and share geospatial information about every aspect of their lives. However, the current practice of geospatial data collection and sharing is often that individuals provide their data for free in order to use services. However, information about locations of individuals can have serious privacy implications. While there was some regulation of location data collection and sharing, current practice is far from ideal for individuals to safely share their location information to service providers.

    An emerging alternative framework for current practice is to allow individuals to offer their location data through data marketplaces. We called these marketplaces geo-marketplaces. Geo-marketplaces raise a number of interesting issues about data ownership, utility, pricing and privacy. In this thesis, we focus on the interplay between utility, privacy and pricing of geospatial data in various settings of geo-marketplaces. More specifically, two important aspects of geo-marketplaces are at the center of interest: location privacy and pricing for various types of location data. Location privacy is essential for geo-marketplaces due to the sensitivity of location data. Pricing is crucial to make geo-marketplace viable, especially when geospatial data can come in many different forms. Thus, geo-marketplaces require efficient algorithms for selling different types of geospatial data with alternative pricing strategies while protecting sellers' location privacy.

    This thesis aims to enable geo-marketplaces with those requirements by investigating different settings of data types and pricing strategies in a geo-marketplace along with privacy considerations. These settings include (a) differentially private data point release with free query where some quantities derived from individuals' data points can be released for free with strong privacy protection, (b) encrypted data point release with fixed-price query where location data points or geo-tagged data objects for a fixed price with their locations advertised in encrypted space, (c) noisy data point release with variable price query where a location data point can be sold at different prices depending on how much noise is added, and (d) degraded trajectory release with variable-price query where a trajectory can be released or sold at different prices depending on how it is degraded. In each setting, we design the marketplace and develop principled methods to price data, protect privacy of owners and maintain utility of data for buyers in order to enable a viable geo-marketplace. In all settings, our proposed design and methods are evaluated by extensive experiments on large real-world datasets to show its practicality.

    Zoom info:

    WebCast Link: https://usc.zoom.us/j/93232846112

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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