The intrusion detection system identifies the legitimate and attackers in the network area. The intrusion detection system is designed in two categories. In the first model a system component is used for monitoring the security of a WSN and diagnosing compromised or vulnerable. Second model is the monitoring or surveillance system for detecting a malicious intruder that invades the network doma...

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...

Alert Fusion is a process of combining alerts from multiple Intrusion Detection Systems to make a decision about the presence of attack or intrusion. A reliable decision from an alert fusion requires that Intrusion detectors involved in the fusion process generates fully reliable alerts. The unreliable alerts from intrusion detectors may completely misleads the decision making process. The exis...

Internet of Things is an ever-growing network of heterogeneous and constraint nodes which are connected to each other and the Internet. Security plays an important role in such networks. Experience has proved that encryption and authentication are not enough for the security of networks and an Intrusion Detection System is required to detect and to prevent attacks from malicious nodes. In this ...

The neurophysiologic basis of near death experience (NDE) is unknown. Clinical observations suggest that REM state intrusion contributes to NDE. Support for the hypothesis follows five lines of evidence: REM intrusion during wakefulness is a frequent normal occurrence, REM intrusion underlies other clinical conditions, NDE elements can be explained by REM intrusion, cardiorespiratory afferents ...

In this paper, we have presented a survey on the different data mining technique of intrusion detection which is basically used for the intrusion detection purpose in the field of data mining. Today intrusion detection in data mining has gain more interest to the researches, there are many intrusion detection issues in data mining like dos attacks, R2L, U2R and probing etc. There are many algor...

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...

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...

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...

As the computer environment changes significantly, several mechanisms such as firewall are developed and intrusion detection system (IDS) is the representative among them. However, because many IDSs are modeled and evaluated with known intrusion patterns, they have inertia not to detect the intrusions which are unknown or transformed. In this paper, we propose an IGA-based method to generate th...