Data mining techniques have been successfully applied in many fields including marketing, manufacturing, process control, fraud detection and network management. In recent years, data mining-based Intrusion Detection Systems (IDS) have demonstrated high accuracy, good generalization to novel types of intrusion, and robust behavior in a changing environment. In data mining based intrusion detect...

Intrusion detection systems (IDSs) must meet the security goals while minimizing risks of wrong detections. In this paper, we study the issue of building a risk-sensitive intrusion detection mode1. To determinate whether a system calls sequence is normal or not, we consider not only the probability of this sequence belonging to normal sequences set or intrusion sequences set, but also the risk ...

An intruder may target the ID scheme first in order to facilitate further malicious activities. For an intrusion-detection system that is operating in real time, an intruder could be exposed if they were simply to disable the IDS, a denial-of-service attack. A corrupted intrusion-detection system, however, might report erroneous information or fail to identify an attack. The consequences could ...

Intrusion behavior has the characteristics of fast upgrade, strong concealment In this paper, an integrated network intrusion detection algorithm by combining. judge the safety of a system or network. (6). Intrusion Detection Systems (IDS) are primarily centered on characteristic probable incidents, observation data. ABSTRACT: Intrusion Detection Systems are designed to detect system attacks Re...

Research in automated computer security intrusion detection, intrusion detection for short, is maturing. Several difficulties remain to be solved before intrusion detection systems become commonplace as part of real-world security solutions. One such difficulty regards the subject of effectiveness, how successful the intrusion detection system is at actually detecting intrusions with a high deg...

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 a topology of neural network intrusion detection system is proposed on which different backpropagation algorithms are benchmarked. The proposed methodology uses sampled data from KddCup99 data set, an intrusion detection attacks database that is a standard for the evaluation of intrusion detection systems. The performance of backpropagation algorithms implemented in batch mode, is...

The goal of this paper is to present designed architecture of intrusion detection system based on events planning and intrusion signature. The article describes problematic of the variation of intrusions and intrusion detection systems. The core of the proposed architecture is intrusion signature matching through petri nets that clasify system behaviour and determine potential intrusion of moni...

Assuring secure and reliable operation of networks has become a priority research area these days because of ever growing dependency on network technology. Intrusion detection systems (IDS) are used as the last line of defense. Intrusion Detection System identifies patterns of known intrusions (misuse detection) or differentiates anomalous network data from normal data (anomaly detection). In t...

This paper examines real-time intrusion detection systems. Intrusion detection systems detect attacks that attempt to compromise the integrity, confidentiality, or availability of a resource [1]. In particular, this paper focuses on intrusion detection approaches, techniques, and systems.