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Black‐hole attack and counter measure in ad hoc networks using traditional routing optimization
Summary Ad hoc networks have constraints like energy, memory, computation power, and communication range which makes the nodes vulnerable for attacks. In this article, black hole attack detection mechanism is carried out on traditional ad hoc on demand distance vector routing (AODV) protocol. Initia...
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Published in: | Concurrency and computation 2023-04, Vol.35 (9), p.n/a |
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container_title | Concurrency and computation |
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creator | Pullagura, Joshua Reginald Dhulipalla, Venkata Rao |
description | Summary
Ad hoc networks have constraints like energy, memory, computation power, and communication range which makes the nodes vulnerable for attacks. In this article, black hole attack detection mechanism is carried out on traditional ad hoc on demand distance vector routing (AODV) protocol. Initially the proposed work proceeded with black‐hole attack configured on conventional AODV protocol. Black‐hole node will give route reply with highest sequence number to entice the sender to create a route through it. By using intruder detection system threshold mechanism, the black‐hole nodes are identified and isolated. In this article, maximal destination sequence number is estimated by using linear regression technique. Performance comparison is carried out with normal, black hole based and black hole detected routing mechanisms. The simulation findings show that that incorporated method enhances network performance by improving QoS under black hole attack. |
doi_str_mv | 10.1002/cpe.7643 |
format | article |
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Ad hoc networks have constraints like energy, memory, computation power, and communication range which makes the nodes vulnerable for attacks. In this article, black hole attack detection mechanism is carried out on traditional ad hoc on demand distance vector routing (AODV) protocol. Initially the proposed work proceeded with black‐hole attack configured on conventional AODV protocol. Black‐hole node will give route reply with highest sequence number to entice the sender to create a route through it. By using intruder detection system threshold mechanism, the black‐hole nodes are identified and isolated. In this article, maximal destination sequence number is estimated by using linear regression technique. Performance comparison is carried out with normal, black hole based and black hole detected routing mechanisms. The simulation findings show that that incorporated method enhances network performance by improving QoS under black hole attack.</description><identifier>ISSN: 1532-0626</identifier><identifier>EISSN: 1532-0634</identifier><identifier>DOI: 10.1002/cpe.7643</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Ad hoc networks ; ad‐hoc ; AODV ; BH_AODV ; Black holes ; D_BH_AODV ; Nodes ; Optimization ; Quality of service architectures</subject><ispartof>Concurrency and computation, 2023-04, Vol.35 (9), p.n/a</ispartof><rights>2023 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2933-1da6b0ab09745e5130a684850286588c0b3d5df88c087d4327f73ea900dbadc33</citedby><cites>FETCH-LOGICAL-c2933-1da6b0ab09745e5130a684850286588c0b3d5df88c087d4327f73ea900dbadc33</cites><orcidid>0000-0003-3270-753X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Pullagura, Joshua Reginald</creatorcontrib><creatorcontrib>Dhulipalla, Venkata Rao</creatorcontrib><title>Black‐hole attack and counter measure in ad hoc networks using traditional routing optimization</title><title>Concurrency and computation</title><description>Summary
Ad hoc networks have constraints like energy, memory, computation power, and communication range which makes the nodes vulnerable for attacks. In this article, black hole attack detection mechanism is carried out on traditional ad hoc on demand distance vector routing (AODV) protocol. Initially the proposed work proceeded with black‐hole attack configured on conventional AODV protocol. Black‐hole node will give route reply with highest sequence number to entice the sender to create a route through it. By using intruder detection system threshold mechanism, the black‐hole nodes are identified and isolated. In this article, maximal destination sequence number is estimated by using linear regression technique. Performance comparison is carried out with normal, black hole based and black hole detected routing mechanisms. The simulation findings show that that incorporated method enhances network performance by improving QoS under black hole attack.</description><subject>Ad hoc networks</subject><subject>ad‐hoc</subject><subject>AODV</subject><subject>BH_AODV</subject><subject>Black holes</subject><subject>D_BH_AODV</subject><subject>Nodes</subject><subject>Optimization</subject><subject>Quality of service architectures</subject><issn>1532-0626</issn><issn>1532-0634</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp1kMtKAzEUhoMoWKvgIwTcuJmay1wySy31AgVd6DqcSTI27XRSkwylrnwEn9EnccaKO1fnPz8fh8OH0DklE0oIu1IbMynylB-gEc04S0jO08O_zPJjdBLCkhBKCacjBDcNqNXXx-fCNQZDjP2GodVYua6NxuO1gdB5g22LQeOFU7g1cev8KuAu2PYVRw_aRutaaLB3XRw6t4l2bd9hqE_RUQ1NMGe_c4xebmfP0_tk_nj3ML2eJ4qVnCdUQ14RqEhZpJnJKCeQi1RkhIk8E0KRiutM10MShU45K-qCGygJ0RVoxfkYXezvbrx760yIcuk6338VJCtESTPBirynLveU8i4Eb2q58XYNficpkYNA2QuUg8AeTfbo1jZm9y8np0-zH_4brxFy6Q</recordid><startdate>20230425</startdate><enddate>20230425</enddate><creator>Pullagura, Joshua Reginald</creator><creator>Dhulipalla, Venkata Rao</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-3270-753X</orcidid></search><sort><creationdate>20230425</creationdate><title>Black‐hole attack and counter measure in ad hoc networks using traditional routing optimization</title><author>Pullagura, Joshua Reginald ; Dhulipalla, Venkata Rao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2933-1da6b0ab09745e5130a684850286588c0b3d5df88c087d4327f73ea900dbadc33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Ad hoc networks</topic><topic>ad‐hoc</topic><topic>AODV</topic><topic>BH_AODV</topic><topic>Black holes</topic><topic>D_BH_AODV</topic><topic>Nodes</topic><topic>Optimization</topic><topic>Quality of service architectures</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pullagura, Joshua Reginald</creatorcontrib><creatorcontrib>Dhulipalla, Venkata Rao</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Concurrency and computation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pullagura, Joshua Reginald</au><au>Dhulipalla, Venkata Rao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Black‐hole attack and counter measure in ad hoc networks using traditional routing optimization</atitle><jtitle>Concurrency and computation</jtitle><date>2023-04-25</date><risdate>2023</risdate><volume>35</volume><issue>9</issue><epage>n/a</epage><issn>1532-0626</issn><eissn>1532-0634</eissn><abstract>Summary
Ad hoc networks have constraints like energy, memory, computation power, and communication range which makes the nodes vulnerable for attacks. In this article, black hole attack detection mechanism is carried out on traditional ad hoc on demand distance vector routing (AODV) protocol. Initially the proposed work proceeded with black‐hole attack configured on conventional AODV protocol. Black‐hole node will give route reply with highest sequence number to entice the sender to create a route through it. By using intruder detection system threshold mechanism, the black‐hole nodes are identified and isolated. In this article, maximal destination sequence number is estimated by using linear regression technique. Performance comparison is carried out with normal, black hole based and black hole detected routing mechanisms. The simulation findings show that that incorporated method enhances network performance by improving QoS under black hole attack.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1002/cpe.7643</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-3270-753X</orcidid></addata></record> |
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subjects | Ad hoc networks ad‐hoc AODV BH_AODV Black holes D_BH_AODV Nodes Optimization Quality of service architectures |
title | Black‐hole attack and counter measure in ad hoc networks using traditional routing optimization |
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