Conference paper Open Access

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

Christiana Ioannou; Vasos Vassiliou


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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>In this paper we evaluate the feasibility of running a lightweight Intrusion Detection System within a constrained sensor or IoT<br>\nnode. 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%.</p>", 
  "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Department of Computer Science, University of Cyprus Nicosia, Cyprus", 
      "@type": "Person", 
      "name": "Christiana Ioannou"
    }, 
    {
      "affiliation": "Department of Computer Science, University of Cyprus Nicosia, Cyprus", 
      "@id": "https://orcid.org/0000-0001-8647-0860", 
      "@type": "Person", 
      "name": "Vasos Vassiliou"
    }
  ], 
  "headline": "An Intrusion Detection System for Constrained WSN and IoT Nodes Based on Binary Logistic Regression", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2018-12-31", 
  "url": "https://zenodo.org/record/2671469", 
  "version": "Accepted pre-print", 
  "keywords": [
    "Wireless Sensor Networks", 
    "Internet of Things", 
    "Intrusion Detection Systems", 
    "Binary Logistic Regression"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.1145/3242102.3242145", 
  "@id": "https://doi.org/10.1145/3242102.3242145", 
  "@type": "ScholarlyArticle", 
  "name": "An Intrusion Detection System for Constrained WSN and IoT Nodes Based on Binary Logistic Regression"
}
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