Network AIS-based DDoS attack detection in SDN environments with NS-3

dc.contributor.advisorKim, Dongsoo
dc.contributor.authorJevtic, Stefan G.
dc.contributor.otherKing, Brian
dc.contributor.otherLuo, Xiao
dc.date.accessioned2017-07-21T17:38:13Z
dc.date.available2017-07-21T17:38:13Z
dc.date.issued2017-07-21
dc.degree.date2017en_US
dc.degree.disciplineElectrical & Computer Engineeringen
dc.degree.grantorPurdue Universityen_US
dc.degree.levelM.S.E.C.E.en_US
dc.descriptionIndiana University-Purdue University Indianapolis (IUPUI)en_US
dc.description.abstractWith the ever increasing connectivity of and dependency on modern computing systems, our civilization is becoming ever more susceptible to cyberattack. To combat this, identifying and disrupting malicious traffic without human intervention becomes essential to protecting our most important systems. To accomplish this, three main tasks for an effective intrusion detection system have been identified: monitor network traffic, categorize and identify anomalous behavior in near real time, and take appropriate action against the identified threat. This system leverages distributed SDN architecture and the principles of Artificial Immune Systems and Self-Organizing Maps to build a network-based intrusion detection system capable of detecting and terminating DDoS attacks in progress.en_US
dc.identifier.doi10.7912/C25W80
dc.identifier.urihttps://hdl.handle.net/1805/13532
dc.identifier.urihttp://dx.doi.org/10.7912/C2/2547
dc.language.isoen_USen_US
dc.rightsAttribution 3.0 United States
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/
dc.subjectDDoSen_US
dc.subjectSDNen_US
dc.subjectSoftware Defined Networkingen_US
dc.subjectNS-3en_US
dc.subjectOpenFlowen_US
dc.titleNetwork AIS-based DDoS attack detection in SDN environments with NS-3en_US
dc.typeThesisen
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