publication . Conference object . 2018

An Intrusion Detection System for Constrained WSN and IoT Nodes Based on Binary Logistic Regression

Christiana Ioannou; Vasos Vassiliou;
Open Access English
  • Published: 31 Dec 2018
  • Publisher: ACM New York
Abstract
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...
Subjects
free text keywords: Wireless Sensor Networks, Internet of Things, Intrusion Detection Systems, Binary Logistic Regression, Statistical analysis, Wireless sensor network, Computer science, Distributed computing, business.industry, business, Logistic regression, Intrusion detection system, Real-time computing, Profiling (computer programming)
Related Organizations
Funded by
EC| RISE
Project
RISE
Research Center on Interactive Media, Smart System and Emerging Technologies
  • Funder: European Commission (EC)
  • Project Code: 739578
  • Funding stream: H2020 | SGA-CSA
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publication . Conference object . 2018

An Intrusion Detection System for Constrained WSN and IoT Nodes Based on Binary Logistic Regression

Christiana Ioannou; Vasos Vassiliou;