In recent decades, the internet has grown and changed the world tremendously, and this, in
turn, has brought about many cyberattacks. Cybersecurity represents one of the most …

The increasing trend toward using the Internet of Things (IoT) increased the number of
intrusions and intruders annually. Hence, the integration, confidentiality, and access to …

Deep learning (DL) is an efficient method for botnet attack detection. However, the volume of
network traffic data and memory space required is usually large. It is, therefore, almost …

The Internet of Things (IoT) is a modern approach that enables connection with a wide
variety of devices remotely. Due to the resource constraints and open nature of IoT nodes …

With the rapid expansion of the use of smartphone devices, malicious attacks against
Android mobile devices have increased. The Android system adopted a wide range of …

Nowadays, hackers take illegal advantage of distributed resources in a network of
computing devices (ie, botnet) to launch cyberattacks against the Internet of Things (IoT) …

Accurate load forecasting is challenging due to the significant uncertainty of load demand.
Deep reinforcement learning, which integrates the nonlinear fitting ability of deep learning …

The need for timely identification of Distributed Denial-of-Service (DDoS) attacks in the
Internet of Things (IoT) has become critical in minimizing security risks as the number of IoT …

In recent years, the use of the internet of things (IoT) has increased dramatically, and
cybersecurity concerns have grown in tandem. Cybersecurity has become a major …

With the continuous occurrence of cybersecurity incidents, network intrusion detection has
become one of the most critical issues in cyber ecosystems. Although previous machine …