Recent advances in the Internet of Things (IoT) are giving rise to a proliferation of
interconnected devices, allowing the use of various smart applications. The enormous …

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

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 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 …

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 …

Cybersecurity is important today because of the increasing growth of the Internet of Things
(IoT), which has resulted in a variety of attacks on computer systems and networks. Cyber …

Software-Defined Networking (SDN) is an emerging paradigm, which evolved in recent
years to address the weaknesses in traditional networks. The significant feature of the SDN …

In this paper, we propose a novel deep learning and blockchain-based energy framework
for smart grids, entitled DeepCoin. The DeepCoin framework uses two schemes, a …

Anomaly detection aims to discover patterns in data that do not conform to the expected
normal behaviour. One of the significant issues for anomaly detection techniques is the …

The rapid evolution and growth of the internet through the last decades led to more concern
about cyber-attacks that are continuously increasing and changing. As a result, an effective …