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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  <dc:creator>Panagiotou, Panos</dc:creator>
  <dc:creator>Mengidis, Notis</dc:creator>
  <dc:creator>Tsikrika, Theodora</dc:creator>
  <dc:creator>Vrochidis, Stefanos</dc:creator>
  <dc:creator>Kompatsiaris, Ioannis</dc:creator>
  <dc:date>2021-10-01</dc:date>
  <dc:description>Cyberattacks are becoming more sophisticated, posing even greater challenges to traditional intrusion detectionEngl methods. Failure to prevent the intrusions could jeopardise security services’ 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.</dc:description>
  <dc:identifier>https://zenodo.org/record/5555915</dc:identifier>
  <dc:identifier>10.11610/isij.5016</dc:identifier>
  <dc:identifier>oai:zenodo.org:5555915</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/830943/</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:title>Host-based Intrusion Detection Using Signature-based and AI-driven Anomaly Detection Methods.</dc:title>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:type>publication-article</dc:type>
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