There is a steep rise in the trend of the utility of Internet technology day by day. This
tremendous increase ushers in a massive amount of data generated and handled. For …

Network security becomes indispensable to our daily interactions and networks. As attackers
continue to develop new types of attacks and the size of networks continues to grow, the …

Featured Application The model proposed in this paper can be deployed to the enterprise
gateway, dynamically monitor network activities, and connect with the firewall to protect the …

The recent increase in hacks and computer network attacks around the world has intensified
the need to develop better intrusion detection and prevention systems. The intrusion …

Study on intrusion detection system (IDS) mostly allow network administrators to focus on
development activities in terms of network security and making better use of resource. Many …

Abstract Machine learning methods are widely used to implement intrusion detection models
for detecting and classifying intrusions in a network or a system. However, many challenges …

A network intrusion detection method combining CNN and BiLSTM network is proposed.
First, the KDD CUP 99 data set is preprocessed by using data extraction algorithm. The data …

In recent times, various machine learning classifiers are used to improve network intrusion
detection. The researchers have proposed many solutions for intrusion detection in the …

Aiming at the problems of fuzzy detection characteristics, high false positive rate and low
accuracy of traditional network intrusion detection technology, an improved intelligent …

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 …