With the increasing frequency, severity and complexity of recent cyber attacks around the
world, network intrusion detection has become mandatory and highly sophisticated task …

In this paper, we survey the published work on machine learning-based network intrusion
detection systems covering recent state-of-the-art techniques. We address the problems of …

Presently, we are living in a hyper-connected world where millions of heterogeneous
devices are continuously sharing information in different application contexts for wellness …

Machine learning and deep learning techniques are widely used to evaluate intrusion
detection systems (IDS) capable of rapidly and automatically recognizing and classifying …

Security remains as a key role in this internet world owing to the fast expansion of users on
the internet. Numerous existing intrusion detection approaches were introduced by …

The need for Network Intrusion Detection systems has risen since usage of cloud
technologies has become mainstream. With the ever growing network traffic, Network …

Abstract The Internet of Things (IoT) has achieved exponential growth worldwide. Although
the IoT is used by millions of users, these networks are handicapped by attacks such as …

To solve the problem of low accuracy and high false‐alarm rate of existing intrusion
detection models for multiple classifications of intrusion behaviors, a network intrusion …

Network intrusion detection is an important technology in national cyberspace security
strategy and has become a research hotspot in various cyberspace security issues in recent …

The use of deep learning models for the network intrusion detection task has been an active
area of research in cybersecurity. Although several excellent surveys cover the growing …