Wireless Sensor Networking is one of the most promising technologies that have
applications ranging from health care to tactical military. Although Wireless Sensor Networks …

Over the last five years there has been an increase in the frequency and diversity of network
attacks. This holds true, as more and more organizations admit compromises on a daily …

The dependency of our society on networked computers has become frightening: In the
economy, all-digital networks have turned from facilitators to drivers; as cyber-physical …

Data mining is an interdisciplinary subfield of computer science involving methods at the
intersection of artificial intelligence, machine learning and statistics. One of the data mining …

The evaluation of computer intrusion detection systems (which we refer to as intrusion
detection systems) is an active research area. In this article, we survey and systematize …

" It also provides a solid, up-to-date reference or self-study tutorial for system engineers,
programmers, system managers, network managers, product marketing personnel, system …

Through the ongoing digitization of the world, the number of connected devices is
continuously growing without any foreseen decline in the near future. In particular, these …

In this paper, we propose XG-BoT, an explainable deep graph neural network model for
botnet node detection. The proposed model comprises a botnet detector and an explainer …

Machine learning (ML), especially deep learning (DL) techniques have been increasingly
used in anomaly-based network intrusion detection systems (NIDS). However, ML/DL has …

The Internet of Things (IoT) offers unprecedented opportunities to access anything from
anywhere and at any time. It is, therefore, not surprising that the IoT acts as a paramount …