Intrusion detection system: overview
Network Intrusion Detection (NID) is the process of identifying network activity that can lead to the compromise of a security policy. In this paper, we will look at four intrusion detection approaches, which include ANN or Artificial Neural Network, SOM, Fuzzy Logic and SVM. ANN is one of the oldes...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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2010
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/4772/1/intrusion_detection_system_overview.pdf |
| _version_ | 1796945181297082368 |
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| author | Alanazi, H. Noor, R.M. Zaidan, B.B. Zaidan, A.A. |
| author_facet | Alanazi, H. Noor, R.M. Zaidan, B.B. Zaidan, A.A. |
| author_sort | Alanazi, H. |
| collection | UM |
| description | Network Intrusion Detection (NID) is the process of identifying network activity that can lead to the compromise of a security policy. In this paper, we will look at four intrusion detection approaches, which include ANN or Artificial Neural Network, SOM, Fuzzy Logic and SVM. ANN is one of the oldest systems that have been used for Intrusion Detection System (IDS), which presents supervised learning methods. However, in this research, we also came across SOM or Self Organizing Map, which is an ANN-based system, but applies unsupervised methods. Another approach is Fuzzy Logic (IDS-based), which also applies unsupervised learning methods. Lastly, we will look at the SVM system or Support Vector Machine for IDS. The goal of this paper is to draw an image for hybrid approaches using these supervised and unsupervised methods |
| first_indexed | 2024-03-06T05:12:50Z |
| format | Article |
| id | um.eprints-4772 |
| institution | Universiti Malaya |
| language | English |
| last_indexed | 2024-03-06T05:12:50Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | um.eprints-47722013-02-13T01:23:47Z http://eprints.um.edu.my/4772/ Intrusion detection system: overview Alanazi, H. Noor, R.M. Zaidan, B.B. Zaidan, A.A. T Technology (General) Network Intrusion Detection (NID) is the process of identifying network activity that can lead to the compromise of a security policy. In this paper, we will look at four intrusion detection approaches, which include ANN or Artificial Neural Network, SOM, Fuzzy Logic and SVM. ANN is one of the oldest systems that have been used for Intrusion Detection System (IDS), which presents supervised learning methods. However, in this research, we also came across SOM or Self Organizing Map, which is an ANN-based system, but applies unsupervised methods. Another approach is Fuzzy Logic (IDS-based), which also applies unsupervised learning methods. Lastly, we will look at the SVM system or Support Vector Machine for IDS. The goal of this paper is to draw an image for hybrid approaches using these supervised and unsupervised methods 2010 Article PeerReviewed application/pdf en http://eprints.um.edu.my/4772/1/intrusion_detection_system_overview.pdf Alanazi, H. and Noor, R.M. and Zaidan, B.B. and Zaidan, A.A. (2010) Intrusion detection system: overview. Journal of Computing, 2 (2). pp. 130-133. ISSN 2151-9617, http://arxiv.org/abs/1002.4047 |
| spellingShingle | T Technology (General) Alanazi, H. Noor, R.M. Zaidan, B.B. Zaidan, A.A. Intrusion detection system: overview |
| title | Intrusion detection system: overview |
| title_full | Intrusion detection system: overview |
| title_fullStr | Intrusion detection system: overview |
| title_full_unstemmed | Intrusion detection system: overview |
| title_short | Intrusion detection system: overview |
| title_sort | intrusion detection system overview |
| topic | T Technology (General) |
| url | http://eprints.um.edu.my/4772/1/intrusion_detection_system_overview.pdf |
| work_keys_str_mv | AT alanazih intrusiondetectionsystemoverview AT noorrm intrusiondetectionsystemoverview AT zaidanbb intrusiondetectionsystemoverview AT zaidanaa intrusiondetectionsystemoverview |