This chapter provides the overview of the state of the art in intrusion detection research. Intrusion detection systems are software and/or hardware components that monitor computer systems and analyze events occurring in them for signs of intrusions. Due to widespread diversity and complexity of computer infrastructures, it is difficult to provide a completely secure computer system. Therefore...

Computer networks are more vulnerable to insider and outsider attacks in recent days due to its widespread use in each field. For that aspect, numbers of security mechanism have been applied to minimize the effect of possible attacks in the network. One of very appealing concept towards network security is intrusion detection system that can able to identify the difference between normal and ab...

Information security and Intrusion Detection System (IDS) plays a critical role in the Internet. IDS is an essential tool for detecting different kinds of attacks in a network and maintaining data integrity, confidentiality and system availability against possible threats. In this paper, a hybrid approach towards achieving high performance is proposed. In fact, the important goal of this paper ...

There exist many problems in intrusion detection systems such as large data volume, features and data redundancy which seriously affect the efficiency of the detection algorithm. Such problems need to be addressed in developing reliable intrusion detection systems. In this paper, we propose an intrusion detection model that combines Rough Set based Feature Selection Algorithm and Fuzzy SVM for ...

Detection of intrusion in network is necessary since the intrusion may create harm or attack any application which needs to be detected and prevented. Although there are various algorithms implemented for the detection of intrusions, but the classification of these intrusion is also an important concern since the type of attack depends on the intrusion. Here in this paper a survey of all the In...

High-dimensional intrusion detection data concentration information redundancy results in lower processing velocity of intrusion detection algorithm. Accordingly, the current study proposes an intrusion feature selection algorithm based on particle swarm optimization (PSO). Analyzing the features of the relevance between network intrusion data allows the PSO algorithm to optimally search in a f...

Intrusion detection, as a complementary mechanism to intrusion prevention, is necessary to secure wireless Mobile Ad hoc Networks (MANETs). In this paper we propose a practical agent-based distributed intrusion detection methodology for MANETs. A two-step intrusion detection procedure has been developed to effectively detect anomalies and identify attack types using distributed intrusion detect...

Applying intrusion detection to the fast growing computational Grid environments improves the security which is considered to be the heart of this new field. Flexible cooperative distributed intrusion detection architecture is introduced that suits and benefits from the underlying computational Grid environment. The proposed architecture was tested using homogeneous distributed intrusion detect...

Intrusion detection is a major research problem in network security. Due to the nonlinear nature of the intrusion attempts, unpredictable behavior of the network traffic and the large number of features in the problem space, intrusion detection systems represent a complicated problem area. Choosing effective and key features for intrusion detection is a very important topic in information secur...

In today’s world, almost everybody is affluent with computers and network based technology is growing by leaps and bounds. So, network security has become very important, rather an inevitable part of computer system. An Intrusion Detection System (IDS) is designed to detect system attacks and classify system activities into normal and abnormal form. Machine learning techniques have been applied...