Deep learning (DL) is gaining significant prevalence in every field of study due to its
domination in training large data sets. However, several applications are utilizing machine …

With the world moving towards being increasingly dependent on computers and automation,
one of the main challenges in the current decade has been to build secure applications …

Abstract In the Industrial Internet of Things (IIoT) in the 5G era, the growth of smart devices
will generate a large amount of data traffic, bringing a huge challenge of network traffic …

As the world moves towards being increasingly dependent on computers and automation,
building secure applications, systems and networks are some of the main challenges faced …

Traffic classification acquired the interest of the Internet community early on. Different
approaches have been proposed to classify Internet traffic to manage both security and …

With the rapidly emerging encryption techniques for network traffic, the classification of
encrypted traffic has increasingly become significantly important in network management …

Abstract Wireless Sensor Networks (WSNs) are developed significantly from the last
decades and attracted the attention of scientific and industrial domains. In WSNs, sensor …

ABSTRACT A hybrid machine learning is a combination of multiple types of machine
learning algorithms for improving the performance of single classifiers. Currently, cyber …

The primary objective of an anonymity tool is to protect the anonymity of its users through the
implementation of strong encryption and obfuscation techniques. As a result, it becomes …

With the development of the Industrial Internet of Things (IIoT), the complex traffic generated
by large-scale IIoT devices presents challenges for traffic analysis. Most of existing deep …