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Conference Paper: HAWK: Halting Anomalies with Weighted choKing to rescue well-behaved TCP sessions from shrew DDoS attacks

TitleHAWK: Halting Anomalies with Weighted choKing to rescue well-behaved TCP sessions from shrew DDoS attacks
Authors
Issue Date2005
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
Lecture Notes In Computer Science, 2005, v. 3619, p. 423-432 How to Cite?
AbstractHigh availability in network services is crucial for effective large-scale distributed computing. While distributed denial-of-service (DDoS) attacks through massive packet flooding have baffled researchers for years, a new type of even more detrimental attack - shrew attacks (periodic intensive packet bursts with low average rate) - has recently been identified. Shrew attacks can significantly degrade well-behaved TCP sessions, repel potential new connections, and are very difficult to detect, not to mention defend against, due to its low average rate. We propose a new stateful adaptive queue management technique called HAWK (Halting Anomaly with Weighted choKing) which works by judiciously identifying malicious shrew packet flows using a small flow table and dropping such packets decisively to halt the attack such that well-behaved TCP sessions can re-gain their bandwidth shares. Our NS-2 based extensive performance results indicate that HAWK is highly agile. © Springer-Verlag Berlin Heidelberg 2005.
Persistent Identifierhttp://hdl.handle.net/10722/99549
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorKwok, YKen_HK
dc.contributor.authorTripathi, Ren_HK
dc.contributor.authorChen, Yen_HK
dc.contributor.authorHwang, Ken_HK
dc.date.accessioned2010-09-25T18:34:57Z-
dc.date.available2010-09-25T18:34:57Z-
dc.date.issued2005en_HK
dc.identifier.citationLecture Notes In Computer Science, 2005, v. 3619, p. 423-432en_HK
dc.identifier.issn0302-9743en_HK
dc.identifier.urihttp://hdl.handle.net/10722/99549-
dc.description.abstractHigh availability in network services is crucial for effective large-scale distributed computing. While distributed denial-of-service (DDoS) attacks through massive packet flooding have baffled researchers for years, a new type of even more detrimental attack - shrew attacks (periodic intensive packet bursts with low average rate) - has recently been identified. Shrew attacks can significantly degrade well-behaved TCP sessions, repel potential new connections, and are very difficult to detect, not to mention defend against, due to its low average rate. We propose a new stateful adaptive queue management technique called HAWK (Halting Anomaly with Weighted choKing) which works by judiciously identifying malicious shrew packet flows using a small flow table and dropping such packets decisively to halt the attack such that well-behaved TCP sessions can re-gain their bandwidth shares. Our NS-2 based extensive performance results indicate that HAWK is highly agile. © Springer-Verlag Berlin Heidelberg 2005.en_HK
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Computer Scienceen_HK
dc.titleHAWK: Halting Anomalies with Weighted choKing to rescue well-behaved TCP sessions from shrew DDoS attacksen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailKwok, YK:ykwok@eee.hku.hken_HK
dc.identifier.authorityKwok, YK=rp00128en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-26444519904en_HK
dc.identifier.hkuros120668en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-26444519904&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume3619en_HK
dc.identifier.spage423en_HK
dc.identifier.epage432en_HK
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridKwok, YK=7101857718en_HK
dc.identifier.scopusauthoridTripathi, R=8908958900en_HK
dc.identifier.scopusauthoridChen, Y=7601429477en_HK
dc.identifier.scopusauthoridHwang, K=7402426691en_HK

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