Southern Illinois University
A SOM+ Diagnostic System for Network Intrusion Detection
Abstract
dc:description.abstract<p>This research created a new theoretical Soft Computing (SC) hybridized network intrusion detection diagnostic system including complex hybridization of a 3D full color Self-Organizing Map (SOM), Artificial Immune System Danger Theory (AISDT), and a Fuzzy Inference System (FIS). This SOM+ diagnostic archetype includes newly defined intrusion types to facilitate diagnostic analysis, a descriptive computational model, and an Invisible Mobile Network Bridge (IMNB) to collect data, while maintaining compatibility with traditional packet analysis. This system is modular, multitaskable, scalable, intuitive, adaptable to quickly changing scenarios, and uses relatively few resources.</p>
Degree
thesis:*- Name thesis:degree_name
- Doctor of Philosophy
- Level thesis:degree_level
- Open Access Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Year dc:date.available
- 2011
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Langin, Chester Louis
- Contributors dc:contributor
-
- Rahimi, Shahram
Subjects
dc:subject × 6Identifiers
dc:identifier.*- Repository record dc:identifier
- https://opensiuc.lib.siu.edu/dissertations/389
- OAI identifier oai:identifier
- oai:opensiuc.lib.siu.edu:dissertations-1389