A Wireless Sensor Network (WSN) consists of spatially distributed autonomous sensors that monitor environmental data such as temperature, humidity, light, speed and sound. WSNs poses new security challenges because of their unattended nature and limited resources. Although prevention measures such as encryption and firewalls have been successfully applied, the attacker can physically access the...

In the information era, as computer networks and related applications become more and more popular, security problems are more and more serious in global information infrastructure. It was reported that in the past two years, large amounts of network attacks and computer viruses caused great damages to global economy and the potential threats to the global information infrastructure have increa...

Intrusion Detection systems (IDSs) have previously been built by hand. These systems have diiculty successfully classifying intruders, and require a signiicant amount of computational overhead making it diicult to create robust real-time IDS systems. Artiicial Intelligence techniques can reduce the human eeort required to build these systems and can improve their performance. Learning and induc...

As complete prevention of computer attacks is not possible, intrusion detection systems (IDSs) play a very important role in minimizing the damage caused by different computer attacks. There are two intrusion detection methods: namely misuseand anomaly-based. A collaborative intelligent intrusion detection system (CIIDS) is proposed to include both methods, since it is concluded from recent res...

The growing need for information sharing among partnering organizations or members of virtual organizations poses a great security challenge. One of the key aspects of this challenge is deploying intrusion detection systems (IDS) that can operate in heterogeneous, large-scale environments. This is particularly difficult because the different networks involved generally use IDSs that have not be...

A taxonomy was developed by Axelsson to define the space of intrusion detection technology and classify IDSs. The taxonomy categorizes IDSs by their detection principle and their operational aspects. The two main categories of detection principles are signature detection and anomaly detection. The remainder of this paper will compare the two categories of detection principles and describe a new...

Intrusion Detection Systems (IDSs) are security tools widely used in computer networks. While they seem to be promising technologies, they pose some serious drawbacks: When utilized in large and high traffic networks, IDSs generate high volumes of low-level alerts which are hardly manageable. Accordingly, there emerged a recent track of security research, focused on alert correlation, which ext...

An important problem in the field of intrusion detection is the management of alerts. Intrusion Detection Systems tend to produce a high number of alerts, most of them being false positives. But producing a high number of alerts does not mean that the attack detection rate is high. In order to increase the detection rate, the use of multiple IDSs based on heterogeneous detection techniques is a...

In the Digital world security is the primary concerned. Today, most discussions on computer security is centered on the tools or techniques used in protecting and defending networks. In recently every organization or company is using intrusion detection systems (IDSs) for detecting malicious attacks. Generally existing commercial IDSs are based on anomaly detection architecture. In anomaly dete...

In this paper we will demonstrate how one can model and analyse Intrusion Detection Systems (IDSs) and their environment using the process algebra Communicating Sequential Processes (CSP) [11, 21] and its model checker FDR [9]. An Intrusion Detection System (IDS) is a system that detects abuses, misuses and unauthorised uses in a network. We show that this analysis can be used to discover two a...