The dynamics of computer networks have changed rapidly over the past few years due to a
tremendous increase in the volume of the connected devices and the corresponding …

Due to the monumental growth of Internet applications in the last decade, the need for
security of information network has increased manifolds. As a primary defense of network …

Anomaly detection in network traffic is one of the key techniques to ensure security in future
networks. Today, the importance of this topic is even higher, since the network traffic is …

Currently, expert systems and applied machine learning algorithms are widely used to
automate network intrusion detection. In critical infrastructure applications of communication …

Recently developed machine learning techniques, with emphasis on deep learning, are
finding their successful implementations in detection and classification of anomalies at both …

The prevalence of internet usage leads to diverse internet traffic, which may contain
information about various types of internet attacks. In recent years, many researchers have …

Because of the complexity of network traffic, there are various significant challenges in the
network anomaly detection fields. One of the major challenges is the lack of labeled training …

In this paper, a hybrid approach of combing two machine learning algorithms is proposed to
detect the different possible attacks by performing effective feature selection and …

The Internet and computer networks are currently suffering from serious security threats.
Those threats often keep changing and will evolve to new unknown variants. In order to …

Anomaly detection in a network is one of the prime concerns for network security. In this
work, a novel Channel Boosted and Residual learning based deep Convolutional Neural …