Artificial Neural Network Approaches to Intrusion Detection: A Review
Intrusion detection systems are the foremost tools for providing safety in computer and network system. There are many limitations in traditional IDSs like time consuming statistical analysis, regular updating, non adaptive, accuracy and flexibility. It is an Artificial Neural Network that supports...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Book Section |
| Language: | English |
| Published: |
World Scientific and Engineering Academy and Society (WSEAS) Stevens Point, Wisconsin, USA
2009
|
| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/496/ http://scholars.utp.edu.my/id/eprint/496/1/ANNAIDS.pdf |
| _version_ | 1848659000702271488 |
|---|---|
| author | Ahmad, iftikhar Azween, Abdullah Alghamdi, Abdullah |
| author2 | Ahmad, Iftikhar |
| author_facet | Ahmad, Iftikhar Ahmad, iftikhar Azween, Abdullah Alghamdi, Abdullah |
| author_sort | Ahmad, iftikhar |
| building | UTP Institutional Repository |
| collection | Online Access |
| description | Intrusion detection systems are the foremost tools for providing safety in computer and network system. There are many limitations in traditional IDSs like time consuming statistical analysis, regular updating, non adaptive, accuracy and flexibility. It is an Artificial Neural Network that supports an ideal specification of an Intrusion Detection System and is a solution to the problems of traditional IDSs. Therefore, An Artificial Neural Network inspired by nervous system has become an interesting tool in the applications of Intrusion Detection Systems due to its promising features. Intrusion detection by Artificial Neural Networks is an ongoing area. In this paper, we provide an introduction and review of the Artificial Neural Network Approaches within Intrusion Detection, in addition to make suggestions for future research. We also discuss on tools and datasets that are being used in Artificial Neural Network Intrusion Detection Systems. This review may help the researcher to develop new optimize approach in the field of Intrusion Detection. |
| first_indexed | 2025-11-13T07:23:28Z |
| format | Book Section |
| id | oai:scholars.utp.edu.my:496 |
| institution | Universiti Teknologi Petronas |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-13T07:23:28Z |
| publishDate | 2009 |
| publisher | World Scientific and Engineering Academy and Society (WSEAS) Stevens Point, Wisconsin, USA |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:scholars.utp.edu.my:4962017-01-19T08:25:23Z http://scholars.utp.edu.my/id/eprint/496/ Artificial Neural Network Approaches to Intrusion Detection: A Review Ahmad, iftikhar Azween, Abdullah Alghamdi, Abdullah QA75 Electronic computers. Computer science Intrusion detection systems are the foremost tools for providing safety in computer and network system. There are many limitations in traditional IDSs like time consuming statistical analysis, regular updating, non adaptive, accuracy and flexibility. It is an Artificial Neural Network that supports an ideal specification of an Intrusion Detection System and is a solution to the problems of traditional IDSs. Therefore, An Artificial Neural Network inspired by nervous system has become an interesting tool in the applications of Intrusion Detection Systems due to its promising features. Intrusion detection by Artificial Neural Networks is an ongoing area. In this paper, we provide an introduction and review of the Artificial Neural Network Approaches within Intrusion Detection, in addition to make suggestions for future research. We also discuss on tools and datasets that are being used in Artificial Neural Network Intrusion Detection Systems. This review may help the researcher to develop new optimize approach in the field of Intrusion Detection. World Scientific and Engineering Academy and Society (WSEAS) Stevens Point, Wisconsin, USA Ahmad, Iftikhar Azween, Abdullah Alghamdi, Abdullah 2009-05-30 Book Section PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/496/1/ANNAIDS.pdf Ahmad, iftikhar and Azween, Abdullah and Alghamdi, Abdullah (2009) Artificial Neural Network Approaches to Intrusion Detection: A Review. In: TELECOMMUNICATIONS and INFORMATICS. World Scientific and Engineering Academy and Society (WSEAS) Stevens Point, Wisconsin, USA , pp. 200-205. ISBN ISBN ~ ISSN:1790-5117 , 978-960-474-084-0. http://portal.acm.org/citation.cfm?id=1561731.1561770# |
| spellingShingle | QA75 Electronic computers. Computer science Ahmad, iftikhar Azween, Abdullah Alghamdi, Abdullah Artificial Neural Network Approaches to Intrusion Detection: A Review |
| title | Artificial Neural Network Approaches to Intrusion Detection: A Review |
| title_full | Artificial Neural Network Approaches to Intrusion Detection: A Review |
| title_fullStr | Artificial Neural Network Approaches to Intrusion Detection: A Review |
| title_full_unstemmed | Artificial Neural Network Approaches to Intrusion Detection: A Review |
| title_short | Artificial Neural Network Approaches to Intrusion Detection: A Review |
| title_sort | artificial neural network approaches to intrusion detection: a review |
| topic | QA75 Electronic computers. Computer science |
| url | http://scholars.utp.edu.my/id/eprint/496/ http://scholars.utp.edu.my/id/eprint/496/ http://scholars.utp.edu.my/id/eprint/496/1/ANNAIDS.pdf |