A comparative analysis of undersampling techniques for network intrusion detection systems design

Neural Network Techniques for Improved Intrusion Detection in Communication Systems

In this paper we discuss the main research approaches in the development of automated and systematic methods for intrusion detection. In this critical overview, the key concept underlying the presented intrusion detection systems is that they involve pattern analysis techniques to discover consistent and useful patterns of system features that describe program and user behaviour, and the set of...

Data Mining Techniques for (Network) Intrusion Detection Systems

In Information Security, intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or availability of a resource. Intrusion detection does not, in general, include prevention of intrusions. In this paper, we are mostly focused on data mining techniques that are being used for such purposes. We debate on the advantages and disadvantages of thes...

Overview of Intrusion Detection Techniques in Database

Data is one of the most valuable assets in today's world and is used in the everyday life of every person and organization. This data stores in a database in order to restore and maintain its efficiently. Since there is a database that can be exploited by SQL injection attacks, internal threats, and unknown threats, there are always concerns about the loss or alteration of data by unauthorized ...

Machine Learning Techniques for Network Intrusion Detection

Most of the currently available network security techniques are not able to cope with the dynamic and increasingly complex nature of cyber attacks on distributed computer systems. Therefore, an automated and adaptive defensive tool is imperative for computer networks. Alongside the existing prevention techniques such as encryption and firewalls, Intrusion Detection System (IDS) has established ...

A Comparative Analysis of Open- Source Intrusion Detection Systems