Immune Multi Agent System for Intrusion Prevention and Self healing System Implement a Non-Linear Classification
Artificial immune systems have recently been implemented in the field of computer security system particularly in intrusion detection and prevention systems. In this paper researchers present an approach to an intrusion prevention system (IPS) which is inspired by the Danger model of immunology. Thi...
| Main Authors: | , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2010
|
| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/2922/ http://scholars.utp.edu.my/id/eprint/2922/1/05561486.pdf |
| _version_ | 1848659326814650368 |
|---|---|
| author | Muna, Elsadig Azween, Abdullah Samir, B. B. |
| author_facet | Muna, Elsadig Azween, Abdullah Samir, B. B. |
| author_sort | Muna, Elsadig |
| building | UTP Institutional Repository |
| collection | Online Access |
| description | Artificial immune systems have recently been implemented in the field of computer security system particularly in intrusion detection and prevention systems. In this paper researchers present an approach to an intrusion prevention system (IPS) which is inspired by the Danger model of immunology. This novel approach used a multi immune agent system that implements a non-linear classification method to identify the abnormality behavior of network system. The authors look into Dendritic Cell (DC) which is a cell in Innate Immune system (IIS) as a classifier cell. Our approach takes the advantages of multi agent system, Dendritic cell, Cluster-K-Nearest-Neighbor, K-mean and Gaussion mixture methods which are give an autonomous, highly accurate and fast classifier security system. This is based on intelligent agents that exploit known functional features of the immune system and the self-healing system to detect, prevent and heal harmful or dangerous events in network systems A combination of features between the IPS and self healing (SH) mechanism to ensure continuity of the networked systems have been established. |
| first_indexed | 2025-11-13T07:28:39Z |
| format | Conference or Workshop Item |
| id | oai:scholars.utp.edu.my:2922 |
| institution | Universiti Teknologi Petronas |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-13T07:28:39Z |
| publishDate | 2010 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:scholars.utp.edu.my:29222012-12-31T04:06:08Z http://scholars.utp.edu.my/id/eprint/2922/ Immune Multi Agent System for Intrusion Prevention and Self healing System Implement a Non-Linear Classification Muna, Elsadig Azween, Abdullah Samir, B. B. QA75 Electronic computers. Computer science Artificial immune systems have recently been implemented in the field of computer security system particularly in intrusion detection and prevention systems. In this paper researchers present an approach to an intrusion prevention system (IPS) which is inspired by the Danger model of immunology. This novel approach used a multi immune agent system that implements a non-linear classification method to identify the abnormality behavior of network system. The authors look into Dendritic Cell (DC) which is a cell in Innate Immune system (IIS) as a classifier cell. Our approach takes the advantages of multi agent system, Dendritic cell, Cluster-K-Nearest-Neighbor, K-mean and Gaussion mixture methods which are give an autonomous, highly accurate and fast classifier security system. This is based on intelligent agents that exploit known functional features of the immune system and the self-healing system to detect, prevent and heal harmful or dangerous events in network systems A combination of features between the IPS and self healing (SH) mechanism to ensure continuity of the networked systems have been established. 2010 Conference or Workshop Item NonPeerReviewed application/zip en http://scholars.utp.edu.my/id/eprint/2922/1/05561486.pdf Muna, Elsadig and Azween, Abdullah and Samir, B. B. (2010) Immune Multi Agent System for Intrusion Prevention and Self healing System Implement a Non-Linear Classification. In: The 4th International Symposium on Information Technology (ITSim 2010), 15-17/06/2010, Kuala Lumpur. |
| spellingShingle | QA75 Electronic computers. Computer science Muna, Elsadig Azween, Abdullah Samir, B. B. Immune Multi Agent System for Intrusion Prevention and Self healing System Implement a Non-Linear Classification |
| title | Immune Multi Agent System for Intrusion Prevention and Self healing System Implement a Non-Linear Classification |
| title_full | Immune Multi Agent System for Intrusion Prevention and Self healing System Implement a Non-Linear Classification |
| title_fullStr | Immune Multi Agent System for Intrusion Prevention and Self healing System Implement a Non-Linear Classification |
| title_full_unstemmed | Immune Multi Agent System for Intrusion Prevention and Self healing System Implement a Non-Linear Classification |
| title_short | Immune Multi Agent System for Intrusion Prevention and Self healing System Implement a Non-Linear Classification |
| title_sort | immune multi agent system for intrusion prevention and self healing system implement a non-linear classification |
| topic | QA75 Electronic computers. Computer science |
| url | http://scholars.utp.edu.my/id/eprint/2922/ http://scholars.utp.edu.my/id/eprint/2922/1/05561486.pdf |