10.1145/3242102.3242145
https://zenodo.org/records/2671469
oai:zenodo.org:2671469
Christiana Ioannou
Christiana Ioannou
Department of Computer Science, University of Cyprus Nicosia, Cyprus
Vasos Vassiliou
Vasos Vassiliou
0000-0001-8647-0860
Department of Computer Science, University of Cyprus Nicosia, Cyprus
An Intrusion Detection System for Constrained WSN and IoT Nodes Based on Binary Logistic Regression
ACM New York
2018
Wireless Sensor Networks
Internet of Things
Intrusion Detection Systems
Binary Logistic Regression
2018-12-31
eng
https://zenodo.org/communities/rise-teaming-cyprus
https://zenodo.org/communities/eu
Accepted pre-print
Creative Commons Attribution Non Commercial No Derivatives 4.0 International
In this paper we evaluate the feasibility of running a lightweight Intrusion Detection System within a constrained sensor or IoT
node. We propose mIDS, which monitors and detects attacks using a statistical analysis tool based on Binary Logistic Regression (BLR). mIDS takes as input only local node parameters for both benign and malicious behavior and derives a normal behavior model that detects abnormalities within the constrained node.We offer a proof of correct operation by testing mIDS in a setting where network-layer attacks are present. In such a system, critical data from the routing layer is obtained and used as a basis for profiling sensor behavior. Our results show that, despite the lightweight implementation, the proposed solution achieves attack detection accuracy levels within the range of 96% - 100%.
This work has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Directorate General for European Programmes, Coordination and Development.
© ACM 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of MSWiM 2018, DOI: https://doi.org/10.1145/3242102.3242145, Christiana Ioannou and Vasos Vassiliou. 2018. An Intrusion Detection System for Constrained WSN and IoT. In the Proceedings of the 21st ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems Montreal(MSWIM '18), QC, Canada — October 28 - November 02, 2018. ACM, New York, NY, USA, 259-263. DOI: https://doi.org/10.1145/3242102. https://www.acm.org/publications/policies/copyright-policy .
European Commission
10.13039/501100000780
739578
Research Center on Interactive Media, Smart System and Emerging Technologies