An Architecture for Enabling Collective Intelligence in IoT Networks

Abstract
Proliferation of the Internet of Things (IoT) has fundamentally changed how different application environments are being used. IoT networks are prone to malicious attacks similar to other networks. Additionally, physical tampering, injection and capturing of the nodes are more probable in IoT networks. Therefore, conventional security practices require substantial re-engineering for IoT networks. Here we present an architecture that enables collective intelligence for IoT networks via smart network nodes and blockchain technology. In this architecture, various security related functionalities are distributed to network nodes to detect tampered, captured and injected devices, recognize their movements and prevent networks’ use as an attack surface. Nodes interact with signaling, security information and data traffic. Security information aids to distribute cyber-security functionalities across the IoT network based on the device and/or application type. Every node in the proposed IoT network does not need to have all the cyber-security functionalities, but the network as a whole needs these functionalities.
Main Authors
Format
Conferences Conference paper
Published
2023
Series
Subjects
Publication in research information system
Publisher
Springer
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202401121255Käytä tätä linkitykseen.
Parent publication ISBN
978-3-031-41455-8
Review status
Peer reviewed
ISSN
0302-9743
DOI
https://doi.org/10.1007/978-3-031-41456-5_3
Conference
International Conference on Computational Collective Intelligence
Language
English
Published in
Lecture Notes in Computer Science
Is part of publication
Computational Collective Intelligence : 15th International Conference, ICCCI 2023, Budapest, Hungary, September 27–29, 2023, Proceedings
Citation
  • Frantti, T., & Şafak, I. (2023). An Architecture for Enabling Collective Intelligence in IoT Networks. In N. T. Nguyen, J. Botzheim, L. Gulyás, M. Núñez, J. Treur, G. Vossen, & A. Kozierkiewicz (Eds.), Computational Collective Intelligence : 15th International Conference, ICCCI 2023, Budapest, Hungary, September 27–29, 2023, Proceedings (pp. 29-42). Springer. Lecture Notes in Computer Science, 14162. https://doi.org/10.1007/978-3-031-41456-5_3
License
In CopyrightOpen Access
Additional information about funding
This work was supported by Business Finland (BF) within the EUREKA CELTIC-NEXT project CISSAN (www.celticnext.eu).
Copyright© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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