NBC-MAIDS: Naïve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks
Internet of Things (IoT) makes physical objects and devices interact with each other through wireless technologies. IoT is expected to deliver a significant role in our lives in near future. However, at the current stage, IoT is vulnerable to various kinds of security threats just like other wired a...
Gespeichert in:
| Veröffentlicht in: | The Journal of supercomputing 2018-10, Vol.74 (10), p.5156-5170 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 5170 |
|---|---|
| container_issue | 10 |
| container_start_page | 5156 |
| container_title | The Journal of supercomputing |
| container_volume | 74 |
| creator | Mehmood, Amjad Mukherjee, Mithun Ahmed, Syed Hassan Song, Houbing Malik, Khalid Mahmood |
| description | Internet of Things (IoT) makes physical objects and devices interact with each other through wireless technologies. IoT is expected to deliver a significant role in our lives in near future. However, at the current stage, IoT is vulnerable to various kinds of security threats just like other wired and wireless networks. Our work mainly focuses on protecting an IoT infrastructure from distributed denial-of-service attacks generated by the intruders. We present a new approach of using Naïve Bayes classification algorithm applied in intrusion detection systems (IDSs). IDSs are deployed in the form of multi-agents throughout the network to sense the misbehaving or irregular traffic and actions of nodes. In the paper, we also discuss the fundamental concepts related to our work and recent research done in similar area. |
| doi_str_mv | 10.1007/s11227-018-2413-7 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2117464911</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2117464911</sourcerecordid><originalsourceid>FETCH-LOGICAL-c359t-7d5c535b17812b5cd4b25d4084c417a34e955b5d966843b3a7541ee8b1b44cb3</originalsourceid><addsrcrecordid>eNp1kMtOAjEUhhujiXh5AHdNXFd7eqEz7rh4IUFdwL7pdAoUoYNtMSHxnXwIX8whmLhydTb__51zPoSugN4Apeo2ATCmCIWCMAGcqCPUAak4oaIQx6hDS0ZJIQU7RWcpLSmlgiveQZ8v_QF57o2Gkzv8Yr6_Phzum51L3gRsVyYlP_PWZN8EnJ1dBP--ddgHvN6usidm7kLGaZeyWxMXorcLV-MWhmdNxMnZbfRhjkfNFJu58SFlPBw2E2xyNvYtXaCTmVkld_k7z9H04X46eCLj18fRoDcmlssyE1VLK7msQBXAKmlrUTFZC1oIK0AZLlwpZSXrststBK-4UVKAc0UFlRC24ufo-oDdxKY9P2W9bLYxtBs1A1CiK0qANgWHlI1NStHN9Cb6tYk7DVTvHeuDY9061nvHWrUdduikzf5RF__I_5d-ACqvfss</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2117464911</pqid></control><display><type>article</type><title>NBC-MAIDS: Naïve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks</title><source>SpringerLink Journals - AutoHoldings</source><creator>Mehmood, Amjad ; Mukherjee, Mithun ; Ahmed, Syed Hassan ; Song, Houbing ; Malik, Khalid Mahmood</creator><creatorcontrib>Mehmood, Amjad ; Mukherjee, Mithun ; Ahmed, Syed Hassan ; Song, Houbing ; Malik, Khalid Mahmood</creatorcontrib><description>Internet of Things (IoT) makes physical objects and devices interact with each other through wireless technologies. IoT is expected to deliver a significant role in our lives in near future. However, at the current stage, IoT is vulnerable to various kinds of security threats just like other wired and wireless networks. Our work mainly focuses on protecting an IoT infrastructure from distributed denial-of-service attacks generated by the intruders. We present a new approach of using Naïve Bayes classification algorithm applied in intrusion detection systems (IDSs). IDSs are deployed in the form of multi-agents throughout the network to sense the misbehaving or irregular traffic and actions of nodes. In the paper, we also discuss the fundamental concepts related to our work and recent research done in similar area.</description><identifier>ISSN: 0920-8542</identifier><identifier>EISSN: 1573-0484</identifier><identifier>DOI: 10.1007/s11227-018-2413-7</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Bayesian analysis ; Classification ; Compilers ; Computer Science ; Cybersecurity ; Denial of service attacks ; Internet of Things ; Interpreters ; Intrusion detection systems ; Multiagent systems ; Processor Architectures ; Programming Languages ; Security management ; Wireless networks</subject><ispartof>The Journal of supercomputing, 2018-10, Vol.74 (10), p.5156-5170</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2018</rights><rights>Copyright Springer Nature B.V. 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c359t-7d5c535b17812b5cd4b25d4084c417a34e955b5d966843b3a7541ee8b1b44cb3</citedby><cites>FETCH-LOGICAL-c359t-7d5c535b17812b5cd4b25d4084c417a34e955b5d966843b3a7541ee8b1b44cb3</cites><orcidid>0000-0003-2631-9223</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11227-018-2413-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11227-018-2413-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids></links><search><creatorcontrib>Mehmood, Amjad</creatorcontrib><creatorcontrib>Mukherjee, Mithun</creatorcontrib><creatorcontrib>Ahmed, Syed Hassan</creatorcontrib><creatorcontrib>Song, Houbing</creatorcontrib><creatorcontrib>Malik, Khalid Mahmood</creatorcontrib><title>NBC-MAIDS: Naïve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks</title><title>The Journal of supercomputing</title><addtitle>J Supercomput</addtitle><description>Internet of Things (IoT) makes physical objects and devices interact with each other through wireless technologies. IoT is expected to deliver a significant role in our lives in near future. However, at the current stage, IoT is vulnerable to various kinds of security threats just like other wired and wireless networks. Our work mainly focuses on protecting an IoT infrastructure from distributed denial-of-service attacks generated by the intruders. We present a new approach of using Naïve Bayes classification algorithm applied in intrusion detection systems (IDSs). IDSs are deployed in the form of multi-agents throughout the network to sense the misbehaving or irregular traffic and actions of nodes. In the paper, we also discuss the fundamental concepts related to our work and recent research done in similar area.</description><subject>Bayesian analysis</subject><subject>Classification</subject><subject>Compilers</subject><subject>Computer Science</subject><subject>Cybersecurity</subject><subject>Denial of service attacks</subject><subject>Internet of Things</subject><subject>Interpreters</subject><subject>Intrusion detection systems</subject><subject>Multiagent systems</subject><subject>Processor Architectures</subject><subject>Programming Languages</subject><subject>Security management</subject><subject>Wireless networks</subject><issn>0920-8542</issn><issn>1573-0484</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp1kMtOAjEUhhujiXh5AHdNXFd7eqEz7rh4IUFdwL7pdAoUoYNtMSHxnXwIX8whmLhydTb__51zPoSugN4Apeo2ATCmCIWCMAGcqCPUAak4oaIQx6hDS0ZJIQU7RWcpLSmlgiveQZ8v_QF57o2Gkzv8Yr6_Phzum51L3gRsVyYlP_PWZN8EnJ1dBP--ddgHvN6usidm7kLGaZeyWxMXorcLV-MWhmdNxMnZbfRhjkfNFJu58SFlPBw2E2xyNvYtXaCTmVkld_k7z9H04X46eCLj18fRoDcmlssyE1VLK7msQBXAKmlrUTFZC1oIK0AZLlwpZSXrststBK-4UVKAc0UFlRC24ufo-oDdxKY9P2W9bLYxtBs1A1CiK0qANgWHlI1NStHN9Cb6tYk7DVTvHeuDY9061nvHWrUdduikzf5RF__I_5d-ACqvfss</recordid><startdate>20181001</startdate><enddate>20181001</enddate><creator>Mehmood, Amjad</creator><creator>Mukherjee, Mithun</creator><creator>Ahmed, Syed Hassan</creator><creator>Song, Houbing</creator><creator>Malik, Khalid Mahmood</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-2631-9223</orcidid></search><sort><creationdate>20181001</creationdate><title>NBC-MAIDS: Naïve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks</title><author>Mehmood, Amjad ; Mukherjee, Mithun ; Ahmed, Syed Hassan ; Song, Houbing ; Malik, Khalid Mahmood</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-7d5c535b17812b5cd4b25d4084c417a34e955b5d966843b3a7541ee8b1b44cb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Bayesian analysis</topic><topic>Classification</topic><topic>Compilers</topic><topic>Computer Science</topic><topic>Cybersecurity</topic><topic>Denial of service attacks</topic><topic>Internet of Things</topic><topic>Interpreters</topic><topic>Intrusion detection systems</topic><topic>Multiagent systems</topic><topic>Processor Architectures</topic><topic>Programming Languages</topic><topic>Security management</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mehmood, Amjad</creatorcontrib><creatorcontrib>Mukherjee, Mithun</creatorcontrib><creatorcontrib>Ahmed, Syed Hassan</creatorcontrib><creatorcontrib>Song, Houbing</creatorcontrib><creatorcontrib>Malik, Khalid Mahmood</creatorcontrib><collection>CrossRef</collection><jtitle>The Journal of supercomputing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mehmood, Amjad</au><au>Mukherjee, Mithun</au><au>Ahmed, Syed Hassan</au><au>Song, Houbing</au><au>Malik, Khalid Mahmood</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>NBC-MAIDS: Naïve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks</atitle><jtitle>The Journal of supercomputing</jtitle><stitle>J Supercomput</stitle><date>2018-10-01</date><risdate>2018</risdate><volume>74</volume><issue>10</issue><spage>5156</spage><epage>5170</epage><pages>5156-5170</pages><issn>0920-8542</issn><eissn>1573-0484</eissn><abstract>Internet of Things (IoT) makes physical objects and devices interact with each other through wireless technologies. IoT is expected to deliver a significant role in our lives in near future. However, at the current stage, IoT is vulnerable to various kinds of security threats just like other wired and wireless networks. Our work mainly focuses on protecting an IoT infrastructure from distributed denial-of-service attacks generated by the intruders. We present a new approach of using Naïve Bayes classification algorithm applied in intrusion detection systems (IDSs). IDSs are deployed in the form of multi-agents throughout the network to sense the misbehaving or irregular traffic and actions of nodes. In the paper, we also discuss the fundamental concepts related to our work and recent research done in similar area.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11227-018-2413-7</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0003-2631-9223</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0920-8542 |
| ispartof | The Journal of supercomputing, 2018-10, Vol.74 (10), p.5156-5170 |
| issn | 0920-8542 1573-0484 |
| language | eng |
| recordid | cdi_proquest_journals_2117464911 |
| source | SpringerLink Journals - AutoHoldings |
| subjects | Bayesian analysis Classification Compilers Computer Science Cybersecurity Denial of service attacks Internet of Things Interpreters Intrusion detection systems Multiagent systems Processor Architectures Programming Languages Security management Wireless networks |
| title | NBC-MAIDS: Naïve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T15%3A43%3A51IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=NBC-MAIDS:%20Na%C3%AFve%20Bayesian%20classification%20technique%20in%20multi-agent%20system-enriched%20IDS%20for%20securing%20IoT%20against%20DDoS%20attacks&rft.jtitle=The%20Journal%20of%20supercomputing&rft.au=Mehmood,%20Amjad&rft.date=2018-10-01&rft.volume=74&rft.issue=10&rft.spage=5156&rft.epage=5170&rft.pages=5156-5170&rft.issn=0920-8542&rft.eissn=1573-0484&rft_id=info:doi/10.1007/s11227-018-2413-7&rft_dat=%3Cproquest_cross%3E2117464911%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2117464911&rft_id=info:pmid/&rfr_iscdi=true |