Generating Privacy Zones in Smart Cities

Smart cities offer a variety of services to provide citizens with efficient transport, water distribution, crime prevention, and traffic control. Such services are personalized by automatically capturing, storing, and processing personally identifiable data. The disclosure of such data to a service provider raises privacy concerns for application users. As a result, research has recognized the need for privacy aware services in smart cities. In this paper we present PrivacyZones, a privacy awareness framework which requires the service provider to share meaningful features of the data collected by their application (such as the number of users in proximity to a location). Using this information an application user will know the potential privacy risk prior to sharing their data. The framework can also recommend the actions a user can take to mitigate privacy risks, such as when, where and what data to share with a service provider. We demonstrate how PrivacyZones could work for two services. First, a Hail-A-Taxi service, with real cell phone and taxi-cab GPS data from the Chinese city, Shenzhen. Second, a Get-A-Discount service with census-income data where inferred income level determines the type of discounts offered to users as they explore a city.