KDD 99 intrusion detection datasets, which are based on DARPA 98 dataset, provides labeled data for researchers working in the field of intrusion detection and is the only labeled dataset publicly available. Numerous researchers employed the datasets in KDD 99 intrusion detection competition to study the utilization of machine learning for intrusion detection and reported detection rates up to ...

The existing well-known network based intrusion detection/ prevention techniques such as the misuse detection technique, etc, are widely used. However, because the misuse detection based intrusion prevention system is proportionally depending on the detection rules, it causes excessive large false alarm which is linked to wrong correspondence. This study suggests an intrusion prevention system ...

Network security is one of the most important issues in the field of computer science. The network intrusion may bring disaster to the network users. It is therefore critical to monitor the network intrusion to prevent the computers from attacking. The intrusion pattern identification is the key point in the intrusion detection. The use of the support vector machine (SVM) can provide intelligen...

This paper presents our statistical based intrusion detection framework for computer networks. This framework uses the six sigma technique to identify the thresholds for the critical network parameters. With the help of raw network data, the thresholds identified are used to differentiate normal, uncertain and abnormal behavior due to network intrusion. This is then used for efficient detection...

In network security, Intrusion Detection System plays a reasonable supplementary role for the firewall. It improves the security and reliability of the computer and helps protect computers from network attacks. At present intrusion detection system analysis module uses the pattern matching technology. In this article, through analyzing the advantages and disadvantages of the main pattern matchi...

Intrusion detection system is one of the possible solutions to timely detect the intrusions and alarm for appropriate action. So far many intrusion detection systems have been proposed for ad-hoc networks, however due to the different characteristics, such intrusion detection systems cannot perform well in wireless mesh networks environment. In this paper, we propose a new framework of intrusio...

In this paper, we present an effective intrusion response engine combined with intrusion detection in ad hoc networks. The intrusion response engine is composed of a secure communication module, a local and a global response module. Its function is based on an innovative tree-based key agreement protocol while the intrusion detection engine is based on a class of neural networks called eSOM. Th...

Today traditional intrusion detection systems are unable to detect intrusion attacks. Huge number of false alarm generated by the system results in financial loss of an organization. The unique features of artificial immune system encourage and motivate the researchers to employ this technique in variety of applications and especially in intrusion detection systems. Recently Artificial immune s...

The network traffic data provided for the design of intrusion detection always are large with ineffective information and enclose limited and ambiguous information about users’ activities. We study the problems and propose a two phases approach in our intrusion detection design. In the first phase, we develop a correlation-based feature selection algorithm to remove the worthless information fr...

The goal of the article is to presents intrusion detections systems and design architecture of intrusion detection based on neural network self organizing map. In the report is described base problematic of neural network and intrusion detection system. The article further deals with specific design of intrusion detection architecture based on user anomaly behavior. A core of the designed archi...