Network intrusion detection is one of the main problems in ensuring the security of modern
computer networks, Wireless Sensor Networks (WSN), and the Internet-of-Things (IoT). In …

Network intrusion detection plays a very important role in protecting computer network
security. The abnormal traffic detection and analysis by extracting the statistical features of …

The emergence of the internet of things (IOT) as a result of the development of the
communications system has made the study of cyber security more important. Day after day …

In this paper, we present a deep neural network model to enhance the intrusion detection
performance. A deep learning architecture combining convolution neural network and long …

In recent years, network traffic data have become larger and more complex, leading to
higher possibilities of network intrusion. Traditional intrusion detection methods face …

Intrusion detection can identify unknown attacks from network traffics and has been an
effective means of network security. Nowadays, existing methods for network anomaly …

Abstract Machine Learning (ML)-based Network Intrusion Detection Systems (NIDSs) have
become a promising tool to protect networks against cyberattacks. A wide range of datasets …

Numerous studies have demonstrated the effectiveness of machine learning techniques in
application to network intrusion detection. And yet, the adoption of machine learning for …

Network Intrusion Detection Systems (NIDSs) are indispensable defensive tools against
various cyberattacks. Lightweight, multipurpose, and anomaly-based detection NIDSs …

Recent breakthroughs in deep learning algorithms have enabled researchers and
practitioners to make significant progress in various hard computer science problems and …