Thesis Open Access

# Minimum Threshold Value Based Jellyfish Periodic Drop Attack Detection Algorithm (MTV-JPDADA) for Mobile Ad Hoc Networks (MANETs)

Dawit, Seyifu Woldehanna

### DataCite XML Export

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<creators>
<creator>
<creatorName>Dawit, Seyifu Woldehanna</creatorName>
<givenName>Seyifu Woldehanna</givenName>
<familyName>Dawit</familyName>
</creator>
</creators>
<titles>
<title>Minimum Threshold Value Based Jellyfish Periodic Drop Attack Detection Algorithm (MTV-JPDADA) for Mobile Ad Hoc Networks (MANETs)</title>
</titles>
<publisher>National Academic Digital Repository of Ethiopia</publisher>
<publicationYear>2019</publicationYear>
<dates>
<date dateType="Issued">2019-06-01</date>
</dates>
<resourceType resourceTypeGeneral="Text">Thesis</resourceType>
<alternateIdentifiers>
</alternateIdentifiers>
<relatedIdentifiers>
<relatedIdentifier relatedIdentifierType="ISBN" relationType="IsPartOf">978-963-313-151-0</relatedIdentifier>
</relatedIdentifiers>
<rightsList>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
</rightsList>
<descriptions>
<description descriptionType="Abstract">&lt;p&gt;Mobile ad hoc network (MANET) is a type of wireless network that operates without dedicated network infrastructure. This kind of network does not have a mechanism to detect malicious users. Due to high vulnerabilities in mobile ad-hoc networks, nodes could be exposed to attacks by malicious nodes. This research study focuses specifically on detecting Jellyfish periodic drop attack in Mobile Ad Hoc Network. The main purpose of the Jellyfish periodic drop attack is to drop the packet sent to the destination node. Thus, the network performance would degrade and weaken the network resources such as computing power and bandwidth considerably decline, which lead the network to be getting worse. This thesis study analyzed the effects of the Jellyfish periodic drop attack on mobile Ad Hoc network based on Ad hoc on-demand distance vector (AODV). The simulation is performed on the basis of performance parameters and its effect is analyzed after adding Jellyfish periodic drop attack nodes in the network. The Performance of our minimum threshold value based Jellyfish periodic drop attack detection algorithm shows that 80.33 % detection rate. Hence, another enhancement like Packet Delivery Ratio, Average End-to-End Delay, and Network Throughput, are improved by 12.40%, 51.13%, and 1.94%, respectively.&lt;/p&gt;</description>
</descriptions>
</resource>

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