Remote to Local Attack Detection Using Supervised Neural Network
In order to determine Remote to Local (R2L) attack, an intrusion detection technique based on artificial neural network is presented. This technique uses sampled dataset from Kddcup99 that is standard for benchmarking of attack detection tools. The backpropagation algorithm is used for training the...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2010
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| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/3083/ http://scholars.utp.edu.my/id/eprint/3083/1/7.pdf |
| _version_ | 1848659348911292416 |
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| author | Iftikhar, Ahmad Azween, Abdullah Abdullah , S. Alghamdi |
| author_facet | Iftikhar, Ahmad Azween, Abdullah Abdullah , S. Alghamdi |
| author_sort | Iftikhar, Ahmad |
| building | UTP Institutional Repository |
| collection | Online Access |
| description | In order to determine Remote to Local (R2L) attack, an intrusion detection technique based on artificial neural network is presented. This technique uses sampled dataset from Kddcup99 that is standard for benchmarking of attack detection tools. The backpropagation algorithm is used for training the feedforward neural network. The developed system is applied to R2L attacks. Moreover, experiment indicates this technique has comparatively low false positive rate and false negative rate, consequently it effectively resolves the deficiency of existing intrusion detection approaches |
| first_indexed | 2025-11-13T07:29:00Z |
| format | Conference or Workshop Item |
| id | oai:scholars.utp.edu.my:3083 |
| institution | Universiti Teknologi Petronas |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-13T07:29:00Z |
| publishDate | 2010 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:scholars.utp.edu.my:30832012-12-31T04:06:50Z http://scholars.utp.edu.my/id/eprint/3083/ Remote to Local Attack Detection Using Supervised Neural Network Iftikhar, Ahmad Azween, Abdullah Abdullah , S. Alghamdi QA75 Electronic computers. Computer science In order to determine Remote to Local (R2L) attack, an intrusion detection technique based on artificial neural network is presented. This technique uses sampled dataset from Kddcup99 that is standard for benchmarking of attack detection tools. The backpropagation algorithm is used for training the feedforward neural network. The developed system is applied to R2L attacks. Moreover, experiment indicates this technique has comparatively low false positive rate and false negative rate, consequently it effectively resolves the deficiency of existing intrusion detection approaches 2010 Conference or Workshop Item NonPeerReviewed application/zip en http://scholars.utp.edu.my/id/eprint/3083/1/7.pdf Iftikhar, Ahmad and Azween, Abdullah and Abdullah , S. Alghamdi (2010) Remote to Local Attack Detection Using Supervised Neural Network. In: The 5th International Conference for Internet Technology and Secured Transactions, 8-11/11, London, UK. |
| spellingShingle | QA75 Electronic computers. Computer science Iftikhar, Ahmad Azween, Abdullah Abdullah , S. Alghamdi Remote to Local Attack Detection Using Supervised Neural Network |
| title | Remote to Local Attack Detection Using Supervised Neural Network |
| title_full | Remote to Local Attack Detection Using Supervised Neural Network |
| title_fullStr | Remote to Local Attack Detection Using Supervised Neural Network |
| title_full_unstemmed | Remote to Local Attack Detection Using Supervised Neural Network |
| title_short | Remote to Local Attack Detection Using Supervised Neural Network |
| title_sort | remote to local attack detection using supervised neural network |
| topic | QA75 Electronic computers. Computer science |
| url | http://scholars.utp.edu.my/id/eprint/3083/ http://scholars.utp.edu.my/id/eprint/3083/1/7.pdf |