The Internet of Things (IoT) paves the way for smart applications such as in E-health, Ehomes, transportation, or energy production. However, IoT technologies also pose privacy challenges for their users, as they allow the tracking and monitoring of the users' behavior and context. The EU General Data Protection Regulation (GDPR) mandates data controller to follow a data protection by design and default approach by implementing for instance pseudonymity for achieving data minimisation. This paper provides a systematic literature review for answering the question of what types of privacy-preserving identifiers are proposed by the literature in IoT environments for implementing pseudonymity. It contributes with classifications and analyses of IoT environments for which privacy-preserving identifiers have been proposed and of the pseudonym types and underlying identity management architectures used. Moreover, it discusses trends and gaps in regard to addressing privacy trade-offs.
In vehicular ad hoc networks (VANETs), vehicles exchange messages to improve traffic and passengers' safety. In VANETs, (passive) adversaries can track vehicles (and their drivers) by analyzing the data exchanged in the network. The use of privacy-enhancing technologies can prevent vehicle tracking but solutions so far proposed either require an intermittent connection to a fixed infrastructure or allow vehicles to generate concurrent pseudonyms which could lead to identity-based (Sybil) attacks. In this paper, we propose an anonymous authentication scheme that does not require a connection to a fixed infrastructure during operation and is not vulnerable to Sybil attacks. Our scheme is built on attribute-based credentials and short lived pseudonyms. In it, vehicles interact with a central authority only once, for registering themselves, and then generate their own pseudonyms without interacting with other devices, or relying on a central authority or a trusted third party. The pseudonyms are periodically refreshed, following system wide epochs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.