This paper applies discriminative multinomial Naïve Bayes with various filtering analysis in order to build a network intrusion detection system. For our experimental analysis, we used the new NSL-KDD dataset, which is considered as a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. We perform 2 class classifications with 10-fold cross validation for building our proposed...

The success of any Intrusion Detection System (IDS) is a complicated problem due to its nonlinearity and the quantitative or qualitative network traffic data stream with numerous features. As a result, in order to get rid of this problem, several types of intrusion detection methods with different levels of accuracy have been proposed which leads the choice of an effective and robust method for...

An Intrusion detection system (IDS) is a device or a software application that monitors a network or systems for malicious activity or policy violations. Intrusion Detection Systems supports to discover, determine, and identify unauthorized use, duplication, alteration, and destruction of information systems. So, to make intrusion detection system more efficient, the techniques that are more ad...

Deep learning based intrusion detection cyber security methods gained increased popularity. The essential element to provide protection the ICT infrastructure is systems (IDSs). Intelligent solutions are necessary control complexity and increase in new attack types. intelligent system (DL/ML) has been widely used with its benefits effectively deal complex great dimensional data. IDS various typ...

Data Mining is a technique to drilling the database for giving meaning to the approachable data. It involves systematic analysis of large data sets. And the classification is used to manage data, sometimes tree modeling of data helps to make predictions about new data. Recently, we have increasing in the number of cyber-attacks, detecting the intrusion in networks become a very tough job. In Ne...

In the field of internet, network based application plays a vital role, where data transfers mostly in digital forms in various formats from source to destinations. In this digital exchange of information there are several possibilities of attacks and vulnerabilities. Intrusion detection systems are widely used to protect networks. An efficient detection of intrusion from network data set is a ...

In this paper we discuss and analyze some of the intelligent classifiers which allows for automatic detection and classification of networks attacks for any intrusion detection system. We will proceed initially with their analysis using the WEKA software to work with the classifiers on a well-known IDS (Intrusion Detection Systems) dataset like NSL-KDD dataset. The NSL-KDD dataset of network at...

By increasing use of computer network and internet using Intrusion Detection System has become more popular. The main drawback of IDS is to generate alert to system administrator based on malicious activities that violates security policies. Recently fuzzy logic plays a vital role in detecting attacks using various rule generation technique. This paper proposed a new concept of using various fu...