Abstract Machine Learning (ML) has been enjoying an unprecedented surge in applications
that solve problems and enable automation in diverse domains. Primarily, this is due to the …

Intrusion detection is one of the important security problems in todays cyber world. A
significant number of techniques have been developed which are based on machine …

In this paper, we present a survey of deep learning approaches for cyber security intrusion
detection, the datasets used, and a comparative study. Specifically, we provide a review of …

The majority of countries rely largely on agriculture for employment. Irrigation accounts for a
sizable amount of water use. Crop irrigation is an important step in crop yield prediction …

The massive growth of data that are transmitted through a variety of devices and
communication protocols have raised serious security concerns, which have increased the …

Deep learning, which is originated from an artificial neural network (ANN), is one of the
major technologies of today's smart cybersecurity systems or policies to function in an …

Network intrusion detection systems (NIDSs) provide a better solution to network security
than other traditional network defense technologies, such as firewall systems. The success …

A great deal of attention has been given to deep learning over the past several years, and
new deep learning techniques are emerging with improved functionality. Many computer …

Nowadays, the ever-increasing complication and severity of security attacks on computer
networks have inspired security researchers to incorporate different machine learning …

Abstract Software Defined Networking Technology (SDN) provides a prospect to effectively
detect and monitor network security problems ascribing to the emergence of the …