PurposeThe aim of this paper is to evaluate the use of blockchain for identity management (IdM) in the context of the Internet of things (IoT) while focusing on privacy-preserving approaches and its applications to healthcare scenarios.Design/methodology/approachThe paper describes the most relevant IdM systems focusing on privacy preserving with or without blockchain and evaluates them against ten selected features grouped into three categories: privacy, usability and IoT. Then, it is important to analyze whether blockchain should be used in all scenarios, according to the importance of each feature for different use cases.FindingsBased on analysis of existing systems, Sovrin is the IdM system that covers more features and is based on blockchain. For each of the evaluated use cases, Sovrin and UniquID were the chosen systems.Research limitations/implicationsThis paper opens new lines of research for IdM systems in IoT, including challenges related to device identity definition, privacy preserving and new security mechanisms.Originality/valueThis paper contributes to the ongoing research in IdM systems for IoT. The adequacy of blockchain is not only analyzed considering the technology; instead the authors analyze its application to real environments considering the required features for each use case.

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Security and privacy concerns are challenging the way users interact with devices. The number of devices connected to a home or enterprise network increases every day. Nowadays, the security of information systems is relevant as user information is constantly being shared and moving in the cloud; however, there are still many problems such as, unsecured web interfaces, weak authentication, insecure networks, lack of encryption, among others, that make services insecure. The software implementations that are currently deployed in companies should have updates and control, as cybersecurity threats increasingly appearing over time. There is already some research towards solutions and methods to predict new attacks or classify variants of previous known attacks, such as (algorithmic) information theory. This survey combines all relevant applications of this topic (also known as Kolmogorov Complexity) in the security and privacy domains. The use of Kolmogorov-based approaches is resource-focused without the need for specific knowledge of the topic under analysis. We have defined a taxonomy with already existing work to classify their different application areas and open up new research questions.

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