An alert fusion model inspired by artificial immune system.
In the recent years one of the most focused topics in the field of network security and more specifically intrusion detection systems was to find a solution to reduce the overwhelming alerts generated by IDSs in the network. Inspired by human defence system and danger theory we propose a complementa...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2012
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| Online Access: | http://psasir.upm.edu.my/id/eprint/27716/ http://psasir.upm.edu.my/id/eprint/27716/1/ID%2027716.pdf |
| _version_ | 1848845917380149248 |
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| author | Mahboubian, Mohammad Udzir, Nur Izura Subramaniam, Shamala Abdul Hamid, Nor Asila Wati |
| author_facet | Mahboubian, Mohammad Udzir, Nur Izura Subramaniam, Shamala Abdul Hamid, Nor Asila Wati |
| author_sort | Mahboubian, Mohammad |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | In the recent years one of the most focused topics in the field of network security and more specifically intrusion detection systems was to find a solution to reduce the overwhelming alerts generated by IDSs in the network. Inspired by human defence system and danger theory we propose a complementary subsystem for IDS which can be integrated into any existing IDS models to aggregate the alerts in order to reduce them, and subsequently reduce false alarms among the alerts. After evaluation using different datasets and attack scenarios, our model managed to aggregate the alerts by the average rate of 97.5 percent. |
| first_indexed | 2025-11-15T08:54:26Z |
| format | Conference or Workshop Item |
| id | upm-27716 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T08:54:26Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-277162014-06-19T07:23:49Z http://psasir.upm.edu.my/id/eprint/27716/ An alert fusion model inspired by artificial immune system. Mahboubian, Mohammad Udzir, Nur Izura Subramaniam, Shamala Abdul Hamid, Nor Asila Wati In the recent years one of the most focused topics in the field of network security and more specifically intrusion detection systems was to find a solution to reduce the overwhelming alerts generated by IDSs in the network. Inspired by human defence system and danger theory we propose a complementary subsystem for IDS which can be integrated into any existing IDS models to aggregate the alerts in order to reduce them, and subsequently reduce false alarms among the alerts. After evaluation using different datasets and attack scenarios, our model managed to aggregate the alerts by the average rate of 97.5 percent. 2012 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/27716/1/ID%2027716.pdf Mahboubian, Mohammad and Udzir, Nur Izura and Subramaniam, Shamala and Abdul Hamid, Nor Asila Wati (2012) An alert fusion model inspired by artificial immune system. In: International Conference on Cyber Security, CyberWarfare and Digital Forensic (CyberSec 2012) , 26-28 June 2012, Kuala Lumpur, Malaysia. (pp. 317-322). English |
| spellingShingle | Mahboubian, Mohammad Udzir, Nur Izura Subramaniam, Shamala Abdul Hamid, Nor Asila Wati An alert fusion model inspired by artificial immune system. |
| title | An alert fusion model inspired by artificial immune system. |
| title_full | An alert fusion model inspired by artificial immune system. |
| title_fullStr | An alert fusion model inspired by artificial immune system. |
| title_full_unstemmed | An alert fusion model inspired by artificial immune system. |
| title_short | An alert fusion model inspired by artificial immune system. |
| title_sort | alert fusion model inspired by artificial immune system. |
| url | http://psasir.upm.edu.my/id/eprint/27716/ http://psasir.upm.edu.my/id/eprint/27716/1/ID%2027716.pdf |