Privacy and Tracking

Abstract

In order for ubiquitous computing to realize its full potential, it is necessary for service providers to detect the presence of user devices to identify the needs and wishes of the associated users—both as this relates to the performance of services and the implementation of privacy preferences. We take a large step in the direction of improving service performance by introducing an approach to tie a person’s online behavior (e.g., as represented by her HTML cookies) with her physical behavior (e.g., location and brick-and-mortar purchases). This enables insights from web browsing to be applied to in-store sales (e.g., using coupons), and data related to user location and behavior to be used to improve the understanding of the user’s online needs. We also show how to tie a user profile to a user communications channel, which enables messaging (e.g., alerts, reminders and coupons) that is tied to the detection of user actions, whether on- or offline. We show how to combine this advance in profiling capabilities with a practically manageable approach to enhance end-user privacy. One aspect of this is an extension of the domain of observations to which users can (or can deny to) grant permissions, e.g., allowing individual users a practical method to determine under what circumstances facial recognition can be used for personalization purposes. Our approach is backwards compatible with existing consumer devices; can be rolled out gradually; and is designed with attention given to the usability of the resulting system.