Anomaly-based intrusion detection is about discerning intrusive and normal patterns of activities based on the normality characterization of information systems. The common goal of anomaly-based intrusion detection is to detect intrusive attacks as many as possible with fewer false alerts. Generally, our work is to study effective models, methods and techniques for anomaly-based intrusion detec...

Intrusion Detection and Prevention System is a must for mobile ad networks as the security mechanisms like encryption, authentication and firewall systems are not able to completely secure the nodes and their communication. In this paper, we aim to study the various intrusion detection and prevention systems that were proposed for Mobile Adhoc Networks (MANETs) and compare the recent techniques...

The Particle Swarm Optimization is very efficient in intrusion detection in the networks. However, many intrusion detection systems either fail to detect or falsely detect the intrusions. This paper proposes a technique for intrusion detection using Particle Swarm Optimization with Genetic Algorithm based feature selection and using Adaptive Mutation for slow convergence of optimization algorit...

In this work, we describe a new framework for an anomaly-based intrusion detection system using system call traces. System calls provide an interface between an application and the operating system’s kernel. Since a program frequently requests services via system calls, a trace of these system calls provides a rich profile of program behavior. But we need to use efficient and effective methods ...

Intrusion Detection Systems (IDS) are software or hardware systems, which automatically monitor network traffic looking for suspicious signs of intrusions. Their aim is to recognise already on-going attacks, and possibly block them, in co-operation with other tools like firewalls, as well. According to data processing, one family of IDS-s is anomaly based intrusion detection systems, which assu...

A Swarm-intelligence-based intrusion detection technique is proposed to in order to reduce the misjudgment & misdetection and increase the real-time response in the existing intrusion detection techniques show. Separating a huge and complicated intrusion detection system into severer independent detection units with unique function so that the amount of detection data processing and the complex...

Hypervisor-based Intrusion Detection Lionel Litty Master of Science Graduate Department of Computer Science University of Toronto 2005 Unauthorized access by intruders to computer systems is a pervasive and seemingly worsening problem. This research explores the implementation of the Intrusion Sensing and Introspection System (ISIS). ISIS is an Intrusion Detection System (IDS) implemented in a ...

In this paper we propose a framework for intrusion detection called Fuzzy Agent-Based Intrusion Detection. A unique feature of our model is that the agents use the fuzzy logic to process log files. This reduces the overhead in a distributed intrusion detection system. We have developed an agent communication architecture that provides a prototype implementation. Key-Words: intrusion detection, ...

As Mobile ad-hoc network (MANET) has become a very important technology the security problem, especially, intrusion detection technique research has attracted many people�s effort. MANET is more vulnerable than wired network and suffers intrusion like wired network. This paper investigated some intrusion detection techniques using machine learning and proposed a profile based neighbor monitorin...

In this paper we propose a framework for multisensor intrusion detection called Fuzzy Agent-Based Intrusion Detection System. A unique feature of this model is that the agent uses data from multiple sensors and the fuzzy logic to process log files. Use of this feature reduces the overhead in a distributed intrusion detection system. We have developed an agent communication architecture that pro...