PrivateBits: managing visual privacy in web browsers

Abstract

Privacy can be an issue during collaboration around a personal display when previous browsing activities become visible within web browser features (e.g., AutoComplete). Users currently lack methods to present only appropriate traces of prior activity in these features. In this paper we explore a semi-automatic approach to privacy management that allows users to classify traces of browsing activity and filter them appropriately when their screen is visible by others. We developed PrivateBits, a prototype web browser that instantiates previously proposed general design guidelines for privacy management systems as well as those specific to web browser visual privacy. A preliminary evaluation found this approach to be flexible enough to meet participants' varying privacy concerns, privacy management strategies, and viewing contexts. However, the results also emphasized the need for additional security features to increase trust in the system and raised questions about how to best manage the tradeoff between ease of use and system concealment.