Smart environments provide users with a large number of new services that will improve their lives, such as smarter and more efficient transportation, advanced smart home services, and pervasive healthcare. Yet, they also have the potential for collecting staggering amounts of personal information, which, if misused, poses a multitude of privacy threats to users ranging from tracking, stalking to monitoring and profiling. Consequently, the users’ right to informational self-determination is at stake in smart environments. Therefore, there is a need for solutions that empower individuals with control over their data in smart environments. Privacy-Enhancing Technologies (PETs) and privacy by design and by default can help to protect users’ privacy. In particular, usable Privacy-Enhancing Identity Management (PE-IdM) can re-establish user control and, thus, informational self-determination by offering users a selection of meaningful preference-based privacy settings that they could choose from to lessen the configuration burden of privacy settings. However, different privacy trade-offs need to be considered and managed for the configuration of the identity management system, as well as various factors influencing users’ privacy preferences. Guidelines for the design of usable management of privacy settings that address varying end-user preferences for control, location sharing and privacy conflicting goals are needed. The objective of this thesis is to propose viable approaches for enforcing usable PE-IdM for smart environments, with a focus on vehicular ad hoc networks (VANETs). To that end, we unravel the technical state of the art regarding the problem space and solutions. We employ qualitative and quantitative empirical Human-Computer Interaction (HCI) research methods to investigate different users’ privacy preferences and factors affecting such preferences. Our results demonstrate a cultural and regional influence on willingness to share location data and preferences for trade-offs for location privacy. Based on our results, we elicit end-users and design requirements and propose high-level design guidelines for usable PE-IdM for VANETs. These guidelines aim to simplify privacy and identity management for users by offering selectable settings that will cater for their different privacy needs and preferences.

Smart environments offer users enhanced services like efficient transportation, smart home features, and pervasive healthcare, but also pose privacy risks by collecting extensive personal information. Consequently, the users’ right to informational self-determination is at stake in smart environments. Privacy-Enhancing Technologies (PETs) and privacy by design and by default can help to protect users’ privacy. In particular, usable Privacy-Enhancing Identity Management (PE-IdM) can re-establish user control by providing preference-based privacy settings to reduce the configuration burden. However, the design of these systems need to consider various privacy trade-offs and the factors influencing users’ preferences. This thesis proposes viable approaches for enforcing usable PE-IdM in smart environments, with a focus on vehicular ad hoc networks (VANETs). We examine the technical state of the art, employ qualitative and quantitative empirical Human-Computer Interaction (HCI) research methods to investigate different users’ privacy preferences and factors affecting such preferences. Based on our results, we elicit end-user design requirements and propose high-level design guidelines for usable PE-IdM for VANETs, aiming to simplify privacy and identity management with selectable settings tailored to diverse privacy needs.