Harnessing ANN for a secure environment
This paper explores recent works in the application of artificial neural network (ANN) for security ? namely, network security via intrusion detection systems, and authentication systems. This paper highlights a variety of approaches that have been adopted in these two distinct areas of study. In th...
| Main Authors: | , |
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| Format: | Article |
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Springer Berlin
2010
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| Online Access: | http://eprints.sunway.edu.my/78/ |
| _version_ | 1848801740033359872 |
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| author | Ling, Mee Hong * Wan, Haslina Hassan* |
| author_facet | Ling, Mee Hong * Wan, Haslina Hassan* |
| author_sort | Ling, Mee Hong * |
| building | SU Institutional Repository |
| collection | Online Access |
| description | This paper explores recent works in the application of artificial neural network (ANN) for security ? namely, network security via intrusion detection systems, and authentication systems. This paper highlights a variety of approaches that have been adopted in these two distinct areas of study. In the application of intrusion detection systems, ANN has been found to be more effective in detecting known attacks over rule-based system; however, only moderate success has been achieved in detecting unknown attacks. For authentication systems, the use of ANN has evolved considerably with hybrid models being developed in recent years. Hybrid ANN, combining different variants of ANN or combining ANN with non-AI techniques, has yielded encouraging results in lowering training time and increasing accuracy. Results suggest that the future of ANN in the deployment of a secure environment may lie in the development of hybrid models that are responsive for real-world applications. |
| first_indexed | 2025-11-14T21:12:15Z |
| format | Article |
| id | sunway-78 |
| institution | Sunway University |
| institution_category | Local University |
| last_indexed | 2025-11-14T21:12:15Z |
| publishDate | 2010 |
| publisher | Springer Berlin |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | sunway-782019-05-14T07:48:30Z http://eprints.sunway.edu.my/78/ Harnessing ANN for a secure environment Ling, Mee Hong * Wan, Haslina Hassan* QA75 Electronic computers. Computer science QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering This paper explores recent works in the application of artificial neural network (ANN) for security ? namely, network security via intrusion detection systems, and authentication systems. This paper highlights a variety of approaches that have been adopted in these two distinct areas of study. In the application of intrusion detection systems, ANN has been found to be more effective in detecting known attacks over rule-based system; however, only moderate success has been achieved in detecting unknown attacks. For authentication systems, the use of ANN has evolved considerably with hybrid models being developed in recent years. Hybrid ANN, combining different variants of ANN or combining ANN with non-AI techniques, has yielded encouraging results in lowering training time and increasing accuracy. Results suggest that the future of ANN in the deployment of a secure environment may lie in the development of hybrid models that are responsive for real-world applications. Springer Berlin 2010 Article PeerReviewed Ling, Mee Hong * and Wan, Haslina Hassan* (2010) Harnessing ANN for a secure environment. Lecture Notes in Computer Science, 6064. pp. 540-547. http://dx.doi.org/10.1007/978-3-642-13318-3_67 |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Ling, Mee Hong * Wan, Haslina Hassan* Harnessing ANN for a secure environment |
| title | Harnessing ANN for a secure environment |
| title_full | Harnessing ANN for a secure environment |
| title_fullStr | Harnessing ANN for a secure environment |
| title_full_unstemmed | Harnessing ANN for a secure environment |
| title_short | Harnessing ANN for a secure environment |
| title_sort | harnessing ann for a secure environment |
| topic | QA75 Electronic computers. Computer science QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.sunway.edu.my/78/ http://eprints.sunway.edu.my/78/ |