Full text
|
PDF
- Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (3MB) | Preview |
An ecological approach to anomaly detection: the EIA Model.
Citation
Pau de la Cruz, Iván and Sánchez García, Sergio and Pinacho, Pedro and Chacón, Max (2012). An ecological approach to anomaly detection: the EIA Model.. In: "ICARIS 2012, 11th International Conference on Artificial Immune Systems", 28/08/2012 - 31/08/2012, Taormina (Italia). ISBN 978-3-642-33756-7. pp. 232-245. https://doi.org/10.1007/978-3-642-33757-4_18.
Description
| Title: | An ecological approach to anomaly detection: the EIA Model. |
|---|---|
| Author/s: |
|
| Item Type: | Presentation at Congress or Conference (Article) |
| Event Title: | ICARIS 2012, 11th International Conference on Artificial Immune Systems |
| Event Dates: | 28/08/2012 - 31/08/2012 |
| Event Location: | Taormina (Italia) |
| Title of Book: | Proceedings of 11th International Conference, ICARIS 2012, Taormina, Italy, August 28-31, 2012 |
| Date: | 2012 |
| ISBN: | 978-3-642-33756-7 |
| Volume: | Lectur |
| Subjects: | |
| Faculty: | E.U.I.T. Telecomunicación (UPM) |
| Department: | Ingeniería y Arquitecturas Telemáticas [hasta 2014] |
| Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
Abstract
The presented work proposes a new approach for anomaly detection. This approach is based on changes in a population of evolving agents under stress. If conditions are appropriate, changes in the population (modeled by the bioindicators) are representative of the alterations to the environment. This approach, based on an ecological view, improves functionally traditional approaches to the detection of anomalies. To verify this assertion, experiments based on Network Intrussion Detection Systems are presented. The results are compared with the behaviour of other bioinspired approaches and machine learning techniques.
More information
| Item ID: | 19767 |
|---|---|
| DC Identifier: | https://oa.upm.es/19767/ |
| OAI Identifier: | oai:oa.upm.es:19767 |
| DOI: | 10.1007/978-3-642-33757-4_18 |
| Official URL: | http://www.artificial-immune-systems.org/icaris/2012/ |
| Deposited by: | Memoria Investigacion |
| Deposited on: | 25 Mar 2014 17:39 |
| Last Modified: | 21 Apr 2016 21:08 |
