Indiana University-Purdue University Indianapolis (IUPUI) / With 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.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/13532 |
| Date | 21 July 2017 |
| Creators | Jevtic, Stefan G. |
| Contributors | Kim, Dongsoo, King, Brian, Luo, Xiao |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Rights | Attribution 3.0 United States, http://creativecommons.org/licenses/by/3.0/us/ |
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