Quality-of-protection (QoP)-an online monitoring and self-protection mechanism
With increasing faults and attacks on the Internet infrastructure, there is an impending need to provide automatic techniques to detect and mitigate the impact of attacks on network services. Denial-of-service attacks have been successful in denying legitimate traffic access to its required resource...
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Veröffentlicht in: | IEEE journal on selected areas in communications 2005-10, Vol.23 (10), p.1983-1993 |
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container_end_page | 1993 |
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container_issue | 10 |
container_start_page | 1983 |
container_title | IEEE journal on selected areas in communications |
container_volume | 23 |
creator | Hariri, S. Guangzhi Qu Modukuri, R. Huoping Chen Yousif, M. |
description | With increasing faults and attacks on the Internet infrastructure, there is an impending need to provide automatic techniques to detect and mitigate the impact of attacks on network services. Denial-of-service attacks have been successful in denying legitimate traffic access to its required resources because existing routing protocols treat the attacking traffic equally as any normal traffic. This paper presents a proactive network defense framework that can be integrated with existing quality-of-service (QoS) protocols to provide differentiated services to network traffic flows based on their distance from the normal behavior. We introduce a new metric that we refer to as abnormality distance (AD) metric that can be used to classify traffic into normal, probable normal, probable abnormal (suspicious traffic), and abnormal (attacking traffic). The AD metric can then be used in conjunction with any QoS protocol to give high priority to normal traffic and lower priority to abnormal traffic. We demonstrate through several examples, how our approach can dynamically detect attacks, quantify their impact, and how to reduce the impacts and recover from them. |
doi_str_mv | 10.1109/JSAC.2005.854122 |
format | Article |
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Denial-of-service attacks have been successful in denying legitimate traffic access to its required resources because existing routing protocols treat the attacking traffic equally as any normal traffic. This paper presents a proactive network defense framework that can be integrated with existing quality-of-service (QoS) protocols to provide differentiated services to network traffic flows based on their distance from the normal behavior. We introduce a new metric that we refer to as abnormality distance (AD) metric that can be used to classify traffic into normal, probable normal, probable abnormal (suspicious traffic), and abnormal (attacking traffic). The AD metric can then be used in conjunction with any QoS protocol to give high priority to normal traffic and lower priority to abnormal traffic. We demonstrate through several examples, how our approach can dynamically detect attacks, quantify their impact, and how to reduce the impacts and recover from them.</description><identifier>ISSN: 0733-8716</identifier><identifier>EISSN: 1558-0008</identifier><identifier>DOI: 10.1109/JSAC.2005.854122</identifier><identifier>CODEN: ISACEM</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Abnormalities ; Abnormality distance (AD) ; Computer crime ; Diffserv networks ; Internet ; IP networks ; Monitoring ; network attack ; Network servers ; Networks ; Priorities ; proactive defense ; Protection ; Protocol (computers) ; Protocols ; Quality of service ; quality-of-protection (QoP) ; Telecommunication traffic ; Traffic engineering ; Traffic flow ; Web and internet services</subject><ispartof>IEEE journal on selected areas in communications, 2005-10, Vol.23 (10), p.1983-1993</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2005</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-fefc05ab7525a6b39134f2cfdbf8f852a61788d8849051d9798e9c2b86521f3f3</citedby><cites>FETCH-LOGICAL-c353t-fefc05ab7525a6b39134f2cfdbf8f852a61788d8849051d9798e9c2b86521f3f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1514527$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1514527$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Hariri, S.</creatorcontrib><creatorcontrib>Guangzhi Qu</creatorcontrib><creatorcontrib>Modukuri, R.</creatorcontrib><creatorcontrib>Huoping Chen</creatorcontrib><creatorcontrib>Yousif, M.</creatorcontrib><title>Quality-of-protection (QoP)-an online monitoring and self-protection mechanism</title><title>IEEE journal on selected areas in communications</title><addtitle>J-SAC</addtitle><description>With increasing faults and attacks on the Internet infrastructure, there is an impending need to provide automatic techniques to detect and mitigate the impact of attacks on network services. Denial-of-service attacks have been successful in denying legitimate traffic access to its required resources because existing routing protocols treat the attacking traffic equally as any normal traffic. This paper presents a proactive network defense framework that can be integrated with existing quality-of-service (QoS) protocols to provide differentiated services to network traffic flows based on their distance from the normal behavior. We introduce a new metric that we refer to as abnormality distance (AD) metric that can be used to classify traffic into normal, probable normal, probable abnormal (suspicious traffic), and abnormal (attacking traffic). The AD metric can then be used in conjunction with any QoS protocol to give high priority to normal traffic and lower priority to abnormal traffic. We demonstrate through several examples, how our approach can dynamically detect attacks, quantify their impact, and how to reduce the impacts and recover from them.</description><subject>Abnormalities</subject><subject>Abnormality distance (AD)</subject><subject>Computer crime</subject><subject>Diffserv networks</subject><subject>Internet</subject><subject>IP networks</subject><subject>Monitoring</subject><subject>network attack</subject><subject>Network servers</subject><subject>Networks</subject><subject>Priorities</subject><subject>proactive defense</subject><subject>Protection</subject><subject>Protocol (computers)</subject><subject>Protocols</subject><subject>Quality of service</subject><subject>quality-of-protection (QoP)</subject><subject>Telecommunication traffic</subject><subject>Traffic engineering</subject><subject>Traffic flow</subject><subject>Web and internet services</subject><issn>0733-8716</issn><issn>1558-0008</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9kTtPwzAURi0EEqWwI7FEDDwGFz_i5GasKp6qgAqYLSe1wVVilzgZ-u9xFSQEA9Ndznd173cQOqZkQikprh5eprMJI0RMQKSUsR00okIAJoTALhqRnHMMOc320UEIK0JomgIbocdFr2rbbbA3eN36Tled9S65WPjnS6xc4l1tnU4a72znW-veE-WWSdD1L7zR1YdyNjSHaM-oOuij7zlGbzfXr7M7PH-6vZ9N57jignfYaFMRocpcMKGykheUp4ZVZlkaMCCYymgOsARICyLossgL0EXFSsgEo4YbPkbnw954xGevQycbGypd18pp3wcJRRa7YDmN5Nm_JAMCaZaRCJ7-AVe-b138QkJWUBZrzSNEBqhqfQitNnLd2ka1G0mJ3HqQWw9y60EOHmLkZIhYrfUPLmgqWM6_ADrAgt8</recordid><startdate>20051001</startdate><enddate>20051001</enddate><creator>Hariri, S.</creator><creator>Guangzhi Qu</creator><creator>Modukuri, R.</creator><creator>Huoping Chen</creator><creator>Yousif, M.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Denial-of-service attacks have been successful in denying legitimate traffic access to its required resources because existing routing protocols treat the attacking traffic equally as any normal traffic. This paper presents a proactive network defense framework that can be integrated with existing quality-of-service (QoS) protocols to provide differentiated services to network traffic flows based on their distance from the normal behavior. We introduce a new metric that we refer to as abnormality distance (AD) metric that can be used to classify traffic into normal, probable normal, probable abnormal (suspicious traffic), and abnormal (attacking traffic). The AD metric can then be used in conjunction with any QoS protocol to give high priority to normal traffic and lower priority to abnormal traffic. We demonstrate through several examples, how our approach can dynamically detect attacks, quantify their impact, and how to reduce the impacts and recover from them.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JSAC.2005.854122</doi><tpages>11</tpages></addata></record> |
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ispartof | IEEE journal on selected areas in communications, 2005-10, Vol.23 (10), p.1983-1993 |
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subjects | Abnormalities Abnormality distance (AD) Computer crime Diffserv networks Internet IP networks Monitoring network attack Network servers Networks Priorities proactive defense Protection Protocol (computers) Protocols Quality of service quality-of-protection (QoP) Telecommunication traffic Traffic engineering Traffic flow Web and internet services |
title | Quality-of-protection (QoP)-an online monitoring and self-protection mechanism |
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