The exponential growth in wireless network faults, vulnerabilities, and attacks make the WLAN security management a challenging research area [29]. Data mining applied to intrusion detection is an active area of research. The main reason for using data mining techniques for intrusion detection systems is due to the enormous volume of existing and newly appearing network data that require proces...

Ad hoc networks have received great attention in recent years, mainly due to their important advantages and their growing demand. Nevertheless, ad hoc networks present many inherent vulnerabilities and demand efficient security mechanisms in order to be safeguarded. An efficient intrusion detection approach combined with an authenticated intrusion response can act as an effective line of defens...

This paper explores the application of probabilistic information retrieval theories to the field of log analysis and host-based intrusion detection. Strong similarities exist between intrusion detection and information retrieval. Using information retrieval techniques may yield significant improvements to the performance of intrusion detection systems. This paper provides a brief review of curr...

Data mining techniques have been successfully applied in many fields including marketing, manufacturing, process control, fraud detection and network management. In recent years, data mining-based Intrusion Detection Systems (IDS) have demonstrated high accuracy, good generalization to novel types of intrusion, and robust behavior in a changing environment. In data mining based intrusion detect...

Intrusion detection system is the indispensable part of every computer. With the increasing attack means, all kinds of intrusion detection methods have appeared. Compared with other intrusion detection methods, the intrusion detection methods based on Conditional Random Fields (CRFs) has better detection effect, but the problems that the accuracy is low when the training data is small and the t...

In this paper, we enhance the functionalities of Snort network-based intrusion detection system to automatically generate patterns of misuse from attack data, and the ability of detecting sequential intrusion behaviors. To that, we implement an intrusion pattern discovery module which applies data mining technique to extract single intrusion patterns and sequential intrusion patterns from a col...

The security of wireless sensor networks is a topic that has been studied extensively in the literature. The intrusion detection system is used to detect various attacks occurring on sensor nodes of Wireless Sensor Networks that are placed in various hostile environments. As many innovative and efficient models have emerged in the last decade in this area, we mainly focus our work on Intrusion ...

The immense advancement in attacks against network give rise to interest in more contentious forms of defense to supplement the existing security approaches. Honeypots are physical or virtual machines successfully used as Intrusion detection tool to detect threats. In this paper we proposed a shadow honeypot based intrusion detection system. Shadow honeypot is used to collect the intrusion from...

Problem statement: Wireless LAN IEEE 802.11 protocols are growing rapidly and security has always been a concern with the security of wired network. Wireless networks encountered threats from unauthorized access to network resources, installation of access points and illegal sniffing (refer as classical intrusion threats). In its current hybrid wired and wireless network attacks on the generall...

Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining a...