<p>Cyber-attacks are rapidly increasing in the internet era due to growth of information technology. The distributed denial service (DDoS) attacks dramatically services cloud networks. In this paper, a new Intrusion Detection System (IDS) is proposed improve performance networks by detecting DDoS effectively wireless work, we propose feature selection method called Split Filter Feature Se...

Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...

These days, network traffic is increasing due to the increasing use of smart devices and the Internet. Amount of the intrusion detection studies focused on feature selection or reduction because some of the features are irrelevant and redundant which results lengthy detection process and degrades the performance of an intrusion detection system (IDS). The purpose of this study is to identify im...

Massive volumes of network traffic & data are generated by common technology including the Internet Things, cloud computing social networking. Intrusion Detection Systems therefore required to track which dynamically analyses incoming traffic. The purpose IDS is carry out attacks inspection or provide security management with desirable help along intrusion data. To date, several approaches ...

As the complexity of network structure increases, so do requirements for architecture are also increasing, and Software Defined Network (SDN) technology has emerged. SDN successfully simplified management, but its open programming nature poses a risk attacks. In complex environments, recognition accuracy traditional models cannot meet speed. view this, this study proposes an attack model based ...

Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...

Nowadays, the massive increment in applications running on a computer and excessive in network services forces to take convenient security policies into an account. Many methods of intrusion detection proposed to provide security in a computer system and network using data mining methods. These methods comprise of the outlier, unsupervised and supervised methods. As we know, each data mining me...

Abstract—The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of ...

In recent years, machine learning-based cyber intrusion detection methods have gained increasing popularity. The number and complexity of new attacks continue to rise; therefore, effective intelligent solutions are necessary. Unsupervised learning techniques particularly appealing systems since they can detect known unknown types as well zero-day attacks. the current paper, we present an unsupe...