Journal article Open Access

Host-based Intrusion Detection Using Signature-based and AI-driven Anomaly Detection Methods.

Panagiotou, Panos; Mengidis, Notis; Tsikrika, Theodora; Vrochidis, Stefanos; Kompatsiaris, Ioannis


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{
  "DOI": "10.11610/isij.5016", 
  "language": "eng", 
  "author": [
    {
      "family": "Panagiotou, Panos"
    }, 
    {
      "family": "Mengidis, Notis"
    }, 
    {
      "family": "Tsikrika, Theodora"
    }, 
    {
      "family": "Vrochidis, Stefanos"
    }, 
    {
      "family": "Kompatsiaris, Ioannis"
    }
  ], 
  "issued": {
    "date-parts": [
      [
        2021, 
        10, 
        1
      ]
    ]
  }, 
  "abstract": "<p>Cyberattacks are becoming more sophisticated, posing even greater challenges to traditional intrusion detectionEngl methods. Failure to prevent the intrusions could jeopardise security services&rsquo; credibility, including data confidentiality, integrity, and availability. Anomaly-based Intrusion Detection Systems and Signature-based Intrusion Detection Systems are two types of systems that have been proposed in the literature to detect security threats. In the current work, a taxonomy of current IDSs is presented, a review of recent works is performed, and we discuss some of the most common datasets used for evaluation. Finally, the survey concludes with a discussion of future IDS research directions and broader observations.</p>", 
  "title": "Host-based Intrusion Detection Using Signature-based and AI-driven Anomaly Detection Methods.", 
  "type": "article-journal", 
  "id": "5555915"
}
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