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dc.contributor.advisorChow, Edward
dc.contributor.authorAlcorn, Joshua Andrew
dc.contributor.committeememberBoult, Terry
dc.contributor.committeememberChang, Sang Yoon
dc.contributor.committeememberBlair, Jean
dc.contributor.committeememberDoerr, Rita
dc.date.accessioned2018-05-09T15:56:35Z
dc.date.available2018-05-09T15:56:35Z
dc.date.submitted2018-05
dc.descriptionIncludes bibliographical references.
dc.description.abstractThe unauthorized access or theft of sensitive, personal information is becoming a weekly news item. The illegal dissemination of proprietary information to media outlets or competitors costs industry untold millions in remediation costs and losses every year. The 2013 data breach at Target, Inc. that impacted 70 million customers is estimated to cost upwards of one billion dollars. Stolen information is also being used to damage political figures and adversely influence foreign and domestic policy. The author offers techniques for better understanding the health and security of our networks. This understanding will help professionals to identify network behavior, anomalies and other latent, systematic issues in their networks. An emerging field of research, Software Defined Networks (SDN) promises to change the landscape of traditional network topology and management. Options are limited for researchers and early adopters in need of adequate SDN testing facilities for their experiments. Industry is responding slowly with embedded support for SDN in their enterprise grade network hardware, but it is cost prohibitive for many test environments with a single SDN switch costing thousands of dollars. There are a few emerging community SDN test networks that are fantastic for testing large topologies with production grade traffic; however, there is a cost associated with membership and some controlled experiments are difficult. A free and indispensable alternative to a dedicated hardware SDN is to use network emulation tools. The author provides a collection of simulation and small-scale testbed tools for use in future research. These software tools provide an amazingly precise representation of physical network nodes and behavior, but are inherently limited by their aggregation with other virtual devices on the same compute node. However, for research requiring a higher precision than software emulation can provide there are few options. The author provides a portable, low-cost, reliable, repeatable solution for this research dilemma.
dc.identifierAlcorn_uccs_0892D_10360.pdf
dc.identifier.urihttps://hdl.handle.net/10976/166925
dc.languageEnglish
dc.publisherUniversity of Colorado Colorado Springs. Kraemer Family Library
dc.relation.ispartofDissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectOpenFlow
dc.subjectSoftware defined networking
dc.subjectSecurity
dc.subjectAnomaly detection
dc.titleCAPITALIZING ON THE SECURITY POTENTIAL OF SOFTWARE DEFINED NETWORKING BY PROVIDING A NETWORK CONFIDENCE ASSESSMENT
dc.typeText
dcterms.cdm.subcollectionComputer Science
thesis.degree.disciplineCollege of Engineering and Applied Science-Computer Science
thesis.degree.grantorUniversity of Colorado Colorado Springs
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)


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