The rapid development of the Internet and smart devices trigger surge in network traffic
making its infrastructure more complex and heterogeneous. The predominated usage of …

Security has become the primary concern in many telecommunications industries today as
risks can have high consequences. Especially, as the core and enable technologies will be …

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 …

In recent years, all real-world processes have been shifted to the cyber environment
practically, and computers communicate with one another over the Internet. As a result, there …

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 …

Despite the growing popularity of machine learning models in the cyber‐security
applications (eg, an intrusion detection system (IDS)), most of these models are perceived …

In recent years, with the rapid development of current Internet and mobile communication
technologies, the infrastructure, devices and resources in networking systems are becoming …

The adoption of network traffic encryption is continually growing. Popular applications use
encryption protocols to secure communications and protect the privacy of users. In addition …

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

Software-defined Networking (SDN) has recently developed and been put forward as a
promising and encouraging solution for future internet architecture. Managed, the …