In order to provide an accurate and timely response to different types of the attacks, intrusion
and anomaly detection systems collect and analyze a lot of data that may include personal …

Nowadays attacks on computer networks continue to advance at a rate outpacing cyber
defenders' ability to write new attack signatures. This paper illustrates a deep learning …

Due to the advance in network technologies, the number of network users is growing rapidly,
which leads to the generation of large network traffic data. This large network traffic data is …

The Internet of Things (IoT) has emerged as a new technological world connecting billions of
devices. Despite providing several benefits, the heterogeneous nature and the extensive …

The Internet of Things (IoT) has proven to be a billion-dollar industry. Despite offering
numerous benefits, the prevalent nature of IoT makes it vulnerable and a possible target for …

Intrusion detection system (IDS) has become an essential layer in all the latest ICT system
due to an urge towards cyber safety in the day-to-day world. Reasons including uncertainty …

Network intrusion detection systems (NIDS) are the most common tool used to detect
malicious attacks on a network. They help prevent the ever-increasing different attacks and …

Big data has a substantial role nowadays, and its importance has significantly increased
over the last decade. Big data's biggest advantages are providing knowledge, supporting …

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

Names: Gupta, Brij, 1982-editor.| Sheng, Quan Z. editor. Title: Machine learning for computer
and cyber security: principles, algorithms, and practices/editors Brij B. Gupta, National …