Towards the Designing of a Robust Intrusion Detection System through an Optimized Advancement of Neural Networks
The duty of securing networks is very difficult due to their size, complexity, diversity and dynamic situation. Currently applying neural networks in intrusion detection is a robust approach to ensure security in the network system. Further, neural networks are alternatives to other approaches in th...
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my.utp.eprints.29972012-12-31T04:06:28Z Towards the Designing of a Robust Intrusion Detection System through an Optimized Advancement of Neural Networks Ahmad, Iftikhar Azween, Abdullah Abdullah , S. Alghamdi QA75 Electronic computers. Computer science The duty of securing networks is very difficult due to their size, complexity, diversity and dynamic situation. Currently applying neural networks in intrusion detection is a robust approach to ensure security in the network system. Further, neural networks are alternatives to other approaches in the area of intrusion detection. The main objective of this research is to present an adaptive, flexible and optimize neural network architecture for intrusion detection system that provides the potential to identify network activity in a robust way. The results of this work give directions to enhance security applications such as Intrusion Detection System (IDS), Intrusion Prevention System (IPS), Adaptive Security Alliance (ASA), check points and firewalls and further guide to the security implementers. SpringerLink 2010 Book Section NonPeerReviewed application/zip http://eprints.utp.edu.my/2997/1/fulltext.pdf Ahmad, Iftikhar and Azween, Abdullah and Abdullah , S. Alghamdi (2010) Towards the Designing of a Robust Intrusion Detection System through an Optimized Advancement of Neural Networks. In: Advances in Computer Science and Information Technology. Lecture Notes in Computer Science, 6059 . SpringerLink , pp. 597-602. http://eprints.utp.edu.my/2997/ |
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QA75 Electronic computers. Computer science Ahmad, Iftikhar Azween, Abdullah Abdullah , S. Alghamdi Towards the Designing of a Robust Intrusion Detection System through an Optimized Advancement of Neural Networks |
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The duty of securing networks is very difficult due to their size, complexity, diversity and dynamic situation. Currently applying neural networks in intrusion detection is a robust approach to ensure security in the network system. Further, neural networks are alternatives to other approaches in the area of intrusion detection. The main objective of this research is to present an adaptive, flexible and optimize neural network architecture for intrusion detection system that provides the potential to identify network activity in a robust way. The results of this work give directions to enhance security applications such as Intrusion Detection System (IDS), Intrusion Prevention System (IPS), Adaptive Security Alliance (ASA), check points and firewalls and further guide to the security implementers. |
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Book Section |
author |
Ahmad, Iftikhar Azween, Abdullah Abdullah , S. Alghamdi |
author_facet |
Ahmad, Iftikhar Azween, Abdullah Abdullah , S. Alghamdi |
author_sort |
Ahmad, Iftikhar |
title |
Towards the Designing of a Robust Intrusion Detection System through an Optimized Advancement of Neural Networks |
title_short |
Towards the Designing of a Robust Intrusion Detection System through an Optimized Advancement of Neural Networks |
title_full |
Towards the Designing of a Robust Intrusion Detection System through an Optimized Advancement of Neural Networks |
title_fullStr |
Towards the Designing of a Robust Intrusion Detection System through an Optimized Advancement of Neural Networks |
title_full_unstemmed |
Towards the Designing of a Robust Intrusion Detection System through an Optimized Advancement of Neural Networks |
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towards the designing of a robust intrusion detection system through an optimized advancement of neural networks |
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2010 |
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http://eprints.utp.edu.my/2997/1/fulltext.pdf http://eprints.utp.edu.my/2997/ |
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