relation: https://khub.utp.edu.my/scholars/1207/
title: Towards the designing of a robust intrusion detection system through an optimized advancement of neural networks
creator: Ahmad, I.
creator: Abdulah, A.B.
creator: Alghamdi, A.S.
description: 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. © 2010 Springer-Verlag.
date: 2010
type: Article
type: PeerReviewed
identifier:   Ahmad, I. and Abdulah, A.B. and Alghamdi, A.S.  (2010) Towards the designing of a robust intrusion detection system through an optimized advancement of neural networks.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6059 L.  pp. 597-602.  ISSN 03029743     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-77954579798&doi=10.1007%2f978-3-642-13577-4_53&partnerID=40&md5=0b53a3ee98bc43e9e331d8db452d6626
relation: 10.1007/978-3-642-13577-4₅₃
identifier: 10.1007/978-3-642-13577-4₅₃