Detection of Syn Flooding Attacks using Linear Prediction Analysis
This paper presents a simple but fast and effective method to detect TCP SYN flooding attacks. Linear prediction analysis is proposed as a new paradigm for DoS attack detection. The proposed SYN flooding detection mechanism makes use of the exponential backoff property of TCP used during timeouts. B...
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| creator | Divakaran, D.M. Murthy, H.A. Gonsalves, T.A. |
| description | This paper presents a simple but fast and effective method to detect TCP SYN flooding attacks. Linear prediction analysis is proposed as a new paradigm for DoS attack detection. The proposed SYN flooding detection mechanism makes use of the exponential backoff property of TCP used during timeouts. By modeling the difference of SYN and SYN+ACK packets, we are successfully able to detect an attack within short delays. We use this method at leaf routers and firewalls to detect the attack without the need of maintaining any state |
| doi_str_mv | 10.1109/ICON.2006.302563 |
| format | Conference Proceeding |
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Linear prediction analysis is proposed as a new paradigm for DoS attack detection. The proposed SYN flooding detection mechanism makes use of the exponential backoff property of TCP used during timeouts. By modeling the difference of SYN and SYN+ACK packets, we are successfully able to detect an attack within short delays. We use this method at leaf routers and firewalls to detect the attack without the need of maintaining any state</description><subject>Computer crime</subject><subject>Computer science</subject><subject>Computer security</subject><subject>Delay</subject><subject>DoS attack</subject><subject>Exponential Backoff</subject><subject>Fault detection</subject><subject>Floods</subject><subject>Large-scale systems</subject><subject>Linear prediction analysis</subject><subject>Mechanical factors</subject><subject>TCP SYN flooding</subject><subject>Traffic control</subject><subject>Web and internet services</subject><issn>1531-2216</issn><issn>2332-5798</issn><isbn>0780397460</isbn><isbn>9780780397460</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjM1KxDAURoM_4DjOXnDTF2i9yU1yk2Wtjg4UR3D2QydJJVpbaeqib68yfpvDgcPH2DWHgnOwt5tq-1wIAF0gCKXxhC0EosgVWXPKLoEMoCWp4YwtuEKeC8H1BVul9A6_k0qi0Qt2dx-m4KY49NnQZq9zn627YfCxf8vKaWrcR8q-05_VsQ_NmL2MwcdjX_ZNN6eYrth523QprP65ZLv1w656yuvt46Yq6zxamHLtBVqvLDqw3FAAZw7CYGi1IE2SgBTRwYETZIg3rVPOOSU9ktehVQqX7OZ4G0MI-68xfjbjvJdgSFvAH6YfSuQ</recordid><startdate>200609</startdate><enddate>200609</enddate><creator>Divakaran, D.M.</creator><creator>Murthy, H.A.</creator><creator>Gonsalves, T.A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200609</creationdate><title>Detection of Syn Flooding Attacks using Linear Prediction Analysis</title><author>Divakaran, D.M. ; Murthy, H.A. ; Gonsalves, T.A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-6d239d593c09187e0c8b283ef627674707577bc0c27871afc5ccc54d37d6ef553</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Computer crime</topic><topic>Computer science</topic><topic>Computer security</topic><topic>Delay</topic><topic>DoS attack</topic><topic>Exponential Backoff</topic><topic>Fault detection</topic><topic>Floods</topic><topic>Large-scale systems</topic><topic>Linear prediction analysis</topic><topic>Mechanical factors</topic><topic>TCP SYN flooding</topic><topic>Traffic control</topic><topic>Web and internet services</topic><toplevel>online_resources</toplevel><creatorcontrib>Divakaran, D.M.</creatorcontrib><creatorcontrib>Murthy, H.A.</creatorcontrib><creatorcontrib>Gonsalves, T.A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Divakaran, D.M.</au><au>Murthy, H.A.</au><au>Gonsalves, T.A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Detection of Syn Flooding Attacks using Linear Prediction Analysis</atitle><btitle>2006 14th IEEE International Conference on Networks</btitle><stitle>ICON</stitle><date>2006-09</date><risdate>2006</risdate><volume>1</volume><spage>1</spage><epage>6</epage><pages>1-6</pages><issn>1531-2216</issn><eissn>2332-5798</eissn><isbn>0780397460</isbn><isbn>9780780397460</isbn><abstract>This paper presents a simple but fast and effective method to detect TCP SYN flooding attacks. Linear prediction analysis is proposed as a new paradigm for DoS attack detection. The proposed SYN flooding detection mechanism makes use of the exponential backoff property of TCP used during timeouts. By modeling the difference of SYN and SYN+ACK packets, we are successfully able to detect an attack within short delays. We use this method at leaf routers and firewalls to detect the attack without the need of maintaining any state</abstract><pub>IEEE</pub><doi>10.1109/ICON.2006.302563</doi><tpages>6</tpages></addata></record> |
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| ispartof | 2006 14th IEEE International Conference on Networks, 2006, Vol.1, p.1-6 |
| issn | 1531-2216 2332-5798 |
| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Computer crime Computer science Computer security Delay DoS attack Exponential Backoff Fault detection Floods Large-scale systems Linear prediction analysis Mechanical factors TCP SYN flooding Traffic control Web and internet services |
| title | Detection of Syn Flooding Attacks using Linear Prediction Analysis |
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