Detecting DDoS Attacks in Software De?ned Networks: An Experimental Study of Stream Sampling Methods

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dc.contributor.advisorSherman, Alan T
dc.contributor.authorHarris, David
dc.contributor.departmentComputer Science and Electrical Engineering
dc.contributor.programComputer Science
dc.date.accessioned2019-10-11T13:43:02Z
dc.date.available2019-10-11T13:43:02Z
dc.date.issued2017-01-01
dc.description.abstractI propose and experimentally evaluate a new sampling method for a streaming algorithm to improve Distributed Denial of Service (DDoS) detection in Software Defined Networks (SDNs). My method leverages the SDN architecture of OpenFlow and its novel capabilities to improve detection by analyzing traffic by flow. This approach can lower the cost of gathering data for analysis and improve the detection rate. Using the Mininet emulation environment, I compare the new sampling methods using my adaption of the hierarchical heavy hitter algorithm in a SDN environment and analyze the differences to a possible implementation on a legacy network. My work shows that clear differences can be detected by using per flow sampling to detect hierarchical heavy hitters from traffic that contains heavy flows.
dc.genretheses
dc.identifierdoi:10.13016/m27nw5-wziw
dc.identifier.other11650
dc.identifier.urihttp://hdl.handle.net/11603/15504
dc.languageen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Theses and Dissertations Collection
dc.relation.ispartofUMBC Graduate School Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please see http://aok.lib.umbc.edu/specoll/repro.php or contact Special Collections at speccoll(at)umbc.edu
dc.sourceOriginal File Name: Harris_umbc_0434M_11650.pdf
dc.subjectDDos
dc.subjectSDN
dc.titleDetecting DDoS Attacks in Software De?ned Networks: An Experimental Study of Stream Sampling Methods
dc.typeText
dcterms.accessRightsDistribution Rights granted to UMBC by the author.

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