Attribute-Based Access Control for the Swarm With Distributed Policy Management

The Internet of Things (IoT) is revolutionizing society by enabling everyday life objects with processing and communication. The Swarm is an edge-centric IoT approach in which independent, cross-niche, and heterogeneous devices can cooperate with each other to execute tasks synergistically. Access c...

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Bibliographic Details
Published in:IEEE transactions on consumer electronics 2019-02, Vol.65 (1), p.90-98
Main Authors: Fedrecheski, Geovane, De Biase, Laisa Caroline Costa, Calcina-Ccori, Pablo C., Zuffo, Marcelo Knorich
Format: Article
Language:English
Subjects:
Access control
Authorization
Consumer electronics
Control systems
Cybersecurity
Density
edge computing
Graphical user interface
Internet of Things
IoT swarm
NIST
Performance evaluation
Scalability
Security management
Usability
usable security
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Summary:The Internet of Things (IoT) is revolutionizing society by enabling everyday life objects with processing and communication. The Swarm is an edge-centric IoT approach in which independent, cross-niche, and heterogeneous devices can cooperate with each other to execute tasks synergistically. Access control is indispensable for the Swarm, as it ensures confidentiality and ownership, and prevents cyber-attacks since only authorized services can communicate. Although many access control models do exist, there is a lack of edge-based and easy-to-use access control systems in the consumer electronics field. This paper presents a distributed attribute-based access control system for the Swarm. It features a distributed policy management GUI that allows users to setup policies for IoT devices in a decentralized way. The proposed system is evaluated according to a set of national institute of standards and technologies quality metrics, and it is also subject to a performance evaluation. Results indicate that the system offers good usability factors and can handle from 10 000 to 6 billion services when considering, respectively, an arbitrary graph density of 20% and a social-based graph density of 0.000034%.
ISSN:0098-3063
1558-4127
DOI:10.1109/TCE.2018.2883382