Quality assessment in industrial applications is often carried out through visual inspection,
usually performed or supported by human domain experts. However, the manual visual …

Software-Defined Network (SDN) has been developed to reduce network complexity
through control and manage the whole network from a centralized location. Today, SDN is …

Abstract Many Intrusion Detection Systems (IDS) has been proposed in the current decade.
To evaluate the effectiveness of the IDS Canadian Institute of Cybersecurity presented a …

The appealing features of Cloud Computing continue to fuel its adoption and its integration
in many sectors such industry, governments, education and entertainment. Nevertheless …

Researchers are motivated to build effective Intrusion Detection Systems because of the
implications of malicious actions in computing, communication, and cyber–physical systems …

The significance of an intrusion detection system (IDS) in networks security cannot be
overstated in detecting and responding to malicious attacks. Failure to detect large-scale …

ABSTRACT A distributed denial of service (DDoS) attack is one of the most common cyber
threats to the Internet of Things (IoT). Several deep learning (DL) techniques have been …

With the rapid development of cloud-edge–terminal (CET) technology, ubiquitous sensing
devices are able to collaborate with edge terminals, enabling real-time, intelligent …

Research of using variety of machine learning techniques to detect malicious traffic is
drawing attention recently. In particular, the acceleration of CNN development used in image …

Today, deep learning approaches are widely used to build Intrusion Detection Systems for
securing IoT environments. However, the models' hidden and complex nature raises various …