INTRUSION Detection systems are now an essential component in the overall network and data security arsenal. With the rapid advancement in the network technologies including higher bandwidths and ease of connectivity of wireless and mobile devices, the focus of intrusion detection has shifted from simple signature matching approaches to detecting attacks based on analyzing contextual informatio...

Intrusions are the activities that violate the security policy of system. Intrusion Detection is the process used to identify intrusions. Network security is to be considered as a major issue in recent years, since the computer network keeps on expanding every day. An Intrusion Detection System (IDS) is a system for detecting intrusions and reporting to the authority or to the network administr...

An intrusion detection ensemble, i.e. a set of diverse intrusion detection algorithms employed as a group, has been shown to outperform each one those diverse algorithms employed individually. Moving along this line, we have devised an intrusion detection ensemble that inspects network packets that flow across the process control network of a digitally controlled physical system such as a power...

Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems (IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problem is amount of Intrusion which is increasing day by day. We need to know about network...

In this work we demonstrate how to model and perform the detection of Distributed Network attacks using NeMODe, a declarative system for Computer Network Intrusion Detection which provides a declarative Domain Specific Language for describing computer network intrusion signatures which span several network packets by stating constraints over network packets, thus, describing relations between s...

The duty of securing networks is very difficult due to their size, complexity, diversity and dynamic situation. Currently applying neural networks in intrusion detection is a robust approach to ensure security in the network system. Further, neural networks are alternatives to other approaches in the area of intrusion detection. The main objective of this research is to present an adaptive, fle...

This paper introduce (ABDIDS), a simple pattern attack ontology that allows agent based intrusion detection system to detect network traffic anomalies at a higher level more than most current intrusion detection systems do. The cooperative agent architecture has been presented. It has been shown how some attributes in network communication can be used to detect attacks. Finally, the benefits of...

In this work we present a domain specific language for network intrusion detection that allows to describe network intrusions composed by several network packets, using a declarative approach to describe the desirable network situations, and based on that description, a set of parameterizations for network intrusion detection mechanisms based on Constraint Programming(CP) will execute to find t...

Complex network and internetwork attacks evade the detection of intrusion detection systems including insertions, evasions and distributed denial of service attacks. The presence of these complex attacks along with false positives in intrusion detection systems has resulted in inefficient detection and response to such packets in current network infrastructure systems. In this paper we analyse ...