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


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="URL">https://zenodo.org/record/5555915</identifier>
  <creators>
    <creator>
      <creatorName>Panagiotou, Panos</creatorName>
      <givenName>Panos</givenName>
      <familyName>Panagiotou</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-1964-3618</nameIdentifier>
      <affiliation>Centre for Research and Technology-Hellas (CERTH), Thessaloniki, Greece</affiliation>
    </creator>
    <creator>
      <creatorName>Mengidis, Notis</creatorName>
      <givenName>Notis</givenName>
      <familyName>Mengidis</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-3588-1007</nameIdentifier>
      <affiliation>Centre for Research and Technology-Hellas (CERTH), Thessaloniki, Greece</affiliation>
    </creator>
    <creator>
      <creatorName>Tsikrika, Theodora</creatorName>
      <givenName>Theodora</givenName>
      <familyName>Tsikrika</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-4148-9028</nameIdentifier>
      <affiliation>Centre for Research and Technology-Hellas (CERTH), Thessaloniki, Greece</affiliation>
    </creator>
    <creator>
      <creatorName>Vrochidis, Stefanos</creatorName>
      <givenName>Stefanos</givenName>
      <familyName>Vrochidis</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-2505-9178</nameIdentifier>
      <affiliation>Centre for Research and Technology-Hellas (CERTH), Thessaloniki, Greece</affiliation>
    </creator>
    <creator>
      <creatorName>Kompatsiaris, Ioannis</creatorName>
      <givenName>Ioannis</givenName>
      <familyName>Kompatsiaris</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-6447-9020</nameIdentifier>
      <affiliation>Centre for Research and Technology-Hellas (CERTH), Thessaloniki, Greece</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Host-based Intrusion Detection Using Signature-based and AI-driven Anomaly Detection Methods.</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <dates>
    <date dateType="Issued">2021-10-01</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5555915</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.11610/isij.5016</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Cyberattacks are becoming more sophisticated, posing even greater challenges to traditional intrusion detectionEngl methods. Failure to prevent the intrusions could jeopardise security services&amp;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.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/830943/">830943</awardNumber>
      <awardTitle>European network of Cybersecurity centres and competence Hub for innovation and Operations</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
23
12
views
downloads
Views 23
Downloads 12
Data volume 12.7 MB
Unique views 22
Unique downloads 11

Share

Cite as