A Distributed Intrusion Detection System Based on Bayesian Alarm Networks
Intrusion Detection in large network must rely on use of many distributed agents instead to one large monolithic module. Agents should have some kind of artificial intelligence in order to cope successfully with different intrusion problems. In this paper, we suggested Bayesian alarm network to work...
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description | Intrusion Detection in large network must rely on use of many distributed agents instead to one large monolithic module. Agents should have some kind of artificial intelligence in order to cope successfully with different intrusion problems. In this paper, we suggested Bayesian alarm network to work as independent Network Intrusion Detection Agent. We have shown that when narrowed in detecting one specific type of the attack in large network, for example denial of service, virus, worm or privacy attack, we can induce much more prior knowledge into system regarding the attack. Different nodes of the network can develop their own model of Bayesian alarm network and agents could communicate between themselves and with common security data base. Networks should be organized hierarchically so on the higher level of hierarchy, Bayesian alarm network, thanks to interconnections with lower level networks and data, acts as a distributed Intrusion Detection System. |
doi_str_mv | 10.1007/3-540-46701-7_19 |
format | Book Chapter |
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Agents should have some kind of artificial intelligence in order to cope successfully with different intrusion problems. In this paper, we suggested Bayesian alarm network to work as independent Network Intrusion Detection Agent. We have shown that when narrowed in detecting one specific type of the attack in large network, for example denial of service, virus, worm or privacy attack, we can induce much more prior knowledge into system regarding the attack. Different nodes of the network can develop their own model of Bayesian alarm network and agents could communicate between themselves and with common security data base. Networks should be organized hierarchically so on the higher level of hierarchy, Bayesian alarm network, thanks to interconnections with lower level networks and data, acts as a distributed Intrusion Detection System.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 9783540668008</identifier><identifier>ISBN: 3540668004</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 3540467017</identifier><identifier>EISBN: 9783540467014</identifier><identifier>DOI: 10.1007/3-540-46701-7_19</identifier><identifier>OCLC: 958524090</identifier><identifier>LCCallNum: QA75.5-76.95</identifier><language>eng</language><publisher>Germany: Springer Berlin / Heidelberg</publisher><subject>Applied sciences ; Bayesian Network ; Computer science; control theory; systems ; Computer systems and distributed systems. User interface ; Exact sciences and technology ; Intrusion Detection ; Intrusion Detection System ; Network Intrusion Detection ; Parse Tree ; Software</subject><ispartof>Lecture notes in computer science, 1999, Vol.1740, p.219-228</ispartof><rights>Springer-Verlag Berlin Heidelberg 1999</rights><rights>2000 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><relation>Lecture Notes in Computer Science</relation></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://ebookcentral.proquest.com/covers/3072689-l.jpg</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/3-540-46701-7_19$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/3-540-46701-7_19$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>309,310,775,776,780,785,786,789,4035,4036,27903,38233,41420,42489</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=1173222$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><contributor>Baumgart, Rainer</contributor><contributor>Siekmann, Jörg</contributor><creatorcontrib>Goos, Gerhard</creatorcontrib><title>A Distributed Intrusion Detection System Based on Bayesian Alarm Networks</title><title>Lecture notes in computer science</title><description>Intrusion Detection in large network must rely on use of many distributed agents instead to one large monolithic module. Agents should have some kind of artificial intelligence in order to cope successfully with different intrusion problems. In this paper, we suggested Bayesian alarm network to work as independent Network Intrusion Detection Agent. We have shown that when narrowed in detecting one specific type of the attack in large network, for example denial of service, virus, worm or privacy attack, we can induce much more prior knowledge into system regarding the attack. Different nodes of the network can develop their own model of Bayesian alarm network and agents could communicate between themselves and with common security data base. Networks should be organized hierarchically so on the higher level of hierarchy, Bayesian alarm network, thanks to interconnections with lower level networks and data, acts as a distributed Intrusion Detection System.</description><subject>Applied sciences</subject><subject>Bayesian Network</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems and distributed systems. User interface</subject><subject>Exact sciences and technology</subject><subject>Intrusion Detection</subject><subject>Intrusion Detection System</subject><subject>Network Intrusion Detection</subject><subject>Parse Tree</subject><subject>Software</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540668008</isbn><isbn>3540668004</isbn><isbn>3540467017</isbn><isbn>9783540467014</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>1999</creationdate><recordtype>book_chapter</recordtype><recordid>eNotkDlTwzAQhcU5mJCe0gWtw-qwjjIkHJnJQAHUGkWWwSSxg6QMk3-PnGSbPd57W3wI3WIYYQBxT4uSQcG4AFwIjdUJuqbpsj-IU5RhjnFBKVNnaKiE7DXOJYA8RxlQIIUSjF6iTJWyJAwUXKFhCD-QihLOSpWh2TifNiH6ZrGNrspnbfTb0HRtPnXR2dhP77sQ3Tp_MCEZ0v5gdi40ps3HK-PX-auLf51fhht0UZtVcMNjH6DPp8ePyUsxf3ueTcbzYoMlUQURwBZUEFOKkjGJubAVtpJVvMYCjJXGAFhOcC2IUpQx7BwYUnGAqqS1oAN0d_i7McGaVe1Na5ugN75ZG7_TGAtKCEm20cEWktJ-Oa8XXbcMGoPu2WqqEy29R6l7tilAj39997t1IWrXJ6xLSMzKfptNdD5oCoJwqTRhmhBB_wEM03Tt</recordid><startdate>1999</startdate><enddate>1999</enddate><creator>Goos, Gerhard</creator><general>Springer Berlin / Heidelberg</general><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>FFUUA</scope><scope>IQODW</scope></search><sort><creationdate>1999</creationdate><title>A Distributed Intrusion Detection System Based on Bayesian Alarm Networks</title><author>Goos, Gerhard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p1829-2704b372a575448167cd1c84d6f170ac8aa00c621f72993441ee0a2d600d53f73</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Applied sciences</topic><topic>Bayesian Network</topic><topic>Computer science; control theory; systems</topic><topic>Computer systems and distributed systems. User interface</topic><topic>Exact sciences and technology</topic><topic>Intrusion Detection</topic><topic>Intrusion Detection System</topic><topic>Network Intrusion Detection</topic><topic>Parse Tree</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Goos, Gerhard</creatorcontrib><collection>ProQuest Ebook Central - Book Chapters - Demo use only</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Goos, Gerhard</au><au>Baumgart, Rainer</au><au>Siekmann, Jörg</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>A Distributed Intrusion Detection System Based on Bayesian Alarm Networks</atitle><btitle>Lecture notes in computer science</btitle><seriestitle>Lecture Notes in Computer Science</seriestitle><date>1999</date><risdate>1999</risdate><volume>1740</volume><spage>219</spage><epage>228</epage><pages>219-228</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540668008</isbn><isbn>3540668004</isbn><eisbn>3540467017</eisbn><eisbn>9783540467014</eisbn><abstract>Intrusion Detection in large network must rely on use of many distributed agents instead to one large monolithic module. Agents should have some kind of artificial intelligence in order to cope successfully with different intrusion problems. In this paper, we suggested Bayesian alarm network to work as independent Network Intrusion Detection Agent. We have shown that when narrowed in detecting one specific type of the attack in large network, for example denial of service, virus, worm or privacy attack, we can induce much more prior knowledge into system regarding the attack. Different nodes of the network can develop their own model of Bayesian alarm network and agents could communicate between themselves and with common security data base. Networks should be organized hierarchically so on the higher level of hierarchy, Bayesian alarm network, thanks to interconnections with lower level networks and data, acts as a distributed Intrusion Detection System.</abstract><cop>Germany</cop><pub>Springer Berlin / Heidelberg</pub><doi>10.1007/3-540-46701-7_19</doi><oclcid>958524090</oclcid><tpages>10</tpages></addata></record> |
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language | eng |
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source | Springer Books |
subjects | Applied sciences Bayesian Network Computer science control theory systems Computer systems and distributed systems. User interface Exact sciences and technology Intrusion Detection Intrusion Detection System Network Intrusion Detection Parse Tree Software |
title | A Distributed Intrusion Detection System Based on Bayesian Alarm Networks |
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