Artificial Neural Network Approaches to Intrusion Detection-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 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.
The rapid expansion of computer networks and mostly of the Internet has created many stability and security problems [1]. During recent years, number of attacks on network has dramatically increased and consequently interest in network intrusion detection has increased among the researchers [2]. The reliance of private and government organizations is increasing on their computer networks and defending theses system from attack is serious. Intrusion detection systems are the foremost tools for providing safety in computer and network system. Because a single intrusion of a computer network can cause a heavy loss or the consistency of network became insecure [3]. Therefore, accurate detection of network attack is very important. For half a century, developers have protected their systems using rules that identify and block specific events. However, the nature of current and future threats urgently requires the development of automated and adaptive IDS [4]. Therefore, An Artificial Neural Network inspired by nervous system has become an interesting tool in the applications of Intrusion Detection Systems. It supports an ideal specification of an Intrusion Detection System and is a solution to the problems of traditional IDSs. Application of ANN in intrusion detection is an ongoing area [5]. In the following sections, we briefly introduce the areas of IDSs, Artificial Neural Networks, and ANN approaches to intrusion detection. Furthermore, research, development and implementation is presented in terms of NN, dataset, system implementation and testing parameter details. At last an overview of this research area is provided, in conjunction with indications for future areas of study.
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