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AN ACCURATE IDENTIFICATION OF PACKET DROPPING ATTACKS USING CAT SWARM OPTIMIZATION (CSO) TO ENSURE BETTER INTRUSION DETECTION IN MANET ENVIRONMENT

Niyaz Hussain A M J; G Maria Priscilla


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  <identifier identifierType="URL">https://zenodo.org/record/5848072</identifier>
  <creators>
    <creator>
      <creatorName>Niyaz Hussain A M J</creatorName>
      <affiliation>Ph.D. Research Scholar,  Department of Computer Science, Sri Ramakrishana College  of Arts &amp; Science (Formerly SNR Sons College),  Coimbatore, Tamilnadu, India / Assistant Professor,  Hindusthan College of Arts and Science, City Campus:   Nava India, Coimbatore - 641028, Tamilnadu, India</affiliation>
    </creator>
    <creator>
      <creatorName>G Maria Priscilla</creatorName>
      <affiliation>Professor &amp; Head, Department of  Computer Science, Sri Ramakrishana College of Arts &amp; Science (Formerly SNR Sons College), Nava India,  Coimbatore 641006, Tamilnadu, India,</affiliation>
    </creator>
  </creators>
  <titles>
    <title>AN ACCURATE IDENTIFICATION OF PACKET  DROPPING ATTACKS USING CAT SWARM  OPTIMIZATION (CSO) TO ENSURE BETTER  INTRUSION DETECTION IN MANET  ENVIRONMENT</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Mobile Ad hoc Network, swarm algorithm, Side Channel Monitoring, packet dropping attack, intrusion detection</subject>
    <subject subjectScheme="issn">2278-3075</subject>
    <subject subjectScheme="handle">100.1/ijitee.A4813119119</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Sponsor">
      <contributorName>Blue Eyes Intelligence Engineering  and Sciences Publication(BEIESP)</contributorName>
      <affiliation>Publisher</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2020-10-30</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5848072</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2278-3075</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijitee.A4813.1091220</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;Mobile Ad hoc Network (MANET), which is comprised of a number of self-organized and battery equipped mobile nodes, is used widely in different applications, like private sectors and military. However, security is a major issue in MANET routing, as the network is prone to attacks. The main objective of intrusion detection system is for categorizing normal and suspicious activities in network. This paper introduce the intrusion detection scheme for establishing the secured path in MANET. For mobile ad hoc networks, swarm optimization approach based novel intrusion detection system is proposed in this paper. The proposed system is based on Cat swarm optimization (CSO) for detecting, one of vey possible attack, i.e. packet dropping attack in mobile ad hoc networks. Also Failure node discovery can be optimized by considering nodes historical information along with the neighbor node information. Before using the swarm optimization for finding sensor node&amp;rsquo;s trust values and for improving provenance data transmission security, an Extend the secure provenance scheme with Side Channel Monitoring &amp;ndash; Information gaining ability (SCM) for detecting packet drop attacks staged by malicious data forwarding nodes is used. It assist in finding presence of selfish nodes as well as packet drop behaviours. With low false positive rate and high true positive rate, packet dropping attacks are detected effectively using proposed technique as shown in simulation results.&lt;/p&gt;</description>
  </descriptions>
</resource>
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