With developing technologies, network security is critical, predominantly active, and distributed ad hoc in networks. An intrusion detection system (IDS) plays a vital role cyber detecting malicious activities traffic. However, class imbalance has triggered challenging issue where many instances of some classes are more than others. Therefore, traditional classifiers suffer classifying result l...

Technological advancements in various industries, such as network intelligence, vehicle networks, e-commerce, the Internet of Things (IoT), ubiquitous computing, and cloud-based applications, have led to an exponential increase volume information flowing through critical systems. As a result, protecting infrastructures from intrusions security threats has become paramount concern field intrusio...

<span lang="EN-US">The identification of abnormal situations in information and telecommunication systems is considered, based on analyze statistical network traffic packages. The method identifying an anomalous situation segmentation data sample proposed. aimed at using classifying algorithms that have the best quality indicators individual segments. proposed will be useful for monitorin...

In all technologies, including traditional computing and cloud computing, security has always been the primary concern. recent years, become widely accepted on a global scale. Cyber attacks aimed at it have increased along with its widespread acceptance. Although ample research is done in domain based rigid fundamentals, advancing network create need for an advanced mechanism. Also, multiclass ...

The enormous increase in the use of Internet daily life has provided an opportunity for intruder attempt to compromise security principles availability, confidentiality, and integrity. As a result, organizations are working level by using attack detection techniques such as Network Intrusion Detection System (NIDS), which monitors analyzes network flow attacks detection. There lot researches pr...

Intrusion detection is one of the main challenges in wireless systems especially in Internet of things (IOT) based networks. There are various attack types such as probe, denial of service, remote to local and user to root. In addition to known attacks and malicious behaviors, there are various unknown attacks that some of them have similar behavior with respect to each other or mimic the norma...

Recently by developing the technology, the number of network-based servicesis increasing, and sensitive information of users is shared through the Internet.Accordingly, large-scale malicious attacks on computer networks could causesevere disruption to network services so cybersecurity turns to a major concern fornetworks. An intrusion detection system (IDS) could be cons...

The primary objective of an intrusion detection system (IDS) is to monitor the network performance and look into any indications malformation over network. While providing high-security IDS played a vital role for past couple years. will fail identify all types attacks, when it comes anomaly detection, often connected with high false alarm rate accuracy very average. Recently, utilize machine l...

Abstract Network security is subject to malicious attacks from multiple sources, and intrusion detection systems play a key role in maintaining network security. During the training of models, results generally have relatively large false rates due shortage data caused by imbalance. To address existing sample imbalance problem, this paper proposes algorithm based on enhanced random forest synth...

Generally, the existing Intrusion Detection Systems (IDS) solutions suffer from low detection accuracy for some attack types compared with overall of attacks. The data imbalance technically affects ratio frequent attacks class (e.g. zero-day attack) to more instances. Therefore, IDS-based machine learning algorithms potentially high false-positive rates. To overcome limitation solutions, a hype...