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UniquID: A Quest to Reconcile Identity Access Management and the IoT
Örebro universitet, Institutionen för naturvetenskap och teknik. (Centre for Applied Autonomous Sensor Systems (AASS), Machine Perception & Interaction)ORCID-id: 0000-0001-9293-7711
UniquID Inc., San Francisco, USA.
Örebro universitet, Institutionen för naturvetenskap och teknik. DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark. (Centre for Applied Autonomous Sensor Systems (AASS))ORCID-id: 0000-0001-9575-2990
2019 (Engelska)Ingår i: Software Technology: Methods and Tools / [ed] Mazzara M., Bruel JM., Meyer B., Petrenko A., Cham: Springer, 2019, s. 237-251Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

The Internet of Things (IoT) has caused a revolutionary paradigm shift in computer networking. After decades of human-centered routines, where devices were merely tools that enabled human beings to authenticate themselves and perform activities, we are now dealing with a device-centered paradigm: the devices themselves are actors, not just tools for people. Conventional identity access management (IAM) frameworks were not designed to handle the challenges of IoT. Trying to use traditional IAM systems to reconcile heterogeneous devices and complex federations of online services (e.g., IoT sensors and cloud computing solutions) adds a cumbersome architectural layer that can become hard to maintain and act as a single point of failure. In this paper, we propose UniquID, a blockchain-based solution that overcomes the need for centralized IAM architectures while providing scalability and robustness. We also present the experimental results of a proof-of-concept UniquID enrolment network, and we discuss two different use-cases that show the considerable value of a blockchain-based IAM.

Ort, förlag, år, upplaga, sidor
Cham: Springer, 2019. s. 237-251
Serie
Lecture Notes in Computer Science (LNCS), ISSN 0302-9743, E-ISSN 1611-3349 ; 11771
Nyckelord [en]
IAM, Identity management systems, Blockchain, Internet of Things, IoT, Machine-to-machine, M2M
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:oru:diva-78932DOI: 10.1007/978-3-030-29852-4_20Scopus ID: 2-s2.0-85075676910ISBN: 978-3-030-29851-7 (tryckt)ISBN: 978-3-030-29852-4 (digital)OAI: oai:DiVA.org:oru-78932DiVA, id: diva2:1384102
Konferens
51st International Conference on Software Technology: Methods and Tools (TOOLS 2019), Innopolis, Russia, October 15-17, 2019
Tillgänglig från: 2020-01-09 Skapad: 2020-01-09 Senast uppdaterad: 2020-01-10Bibliografiskt granskad

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