Globally, the external internet is increasingly being connected to industrial control systems.
As a result, there is an immediate need to protect these networks from a variety of threats …

Globally, the external Internet is increasingly being connected to the contemporary industrial
control system. As a result, there is an immediate need to protect the network from several …

In 2016, Google introduced the concept of Federated Learning (FL), enabling collaborative
Machine Learning (ML). FL does not share local data but ML models, offering applications in …

Traditional machine learning models used for network intrusion detection systems rely on
vast amounts of network traffic data with expertly engineered features. The abundance of …

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 …

Generative Artificial Intelligence (GAI) has recently emerged as a promising solution to
address critical challenges of blockchain technology, including scalability, security, privacy …

With the widespread of cyber attacks, network intrusion detection system (NIDS) is becoming
an important and essential tool to protect Internet of Things (IoT) environments. However, it …

In the healthcare sector, cyberattack detection systems are crucial for ensuring the privacy of
patient data and building trust in the increasingly connected world of medical devices and …

In today's world, it is vital to have strong cybersecurity measures in place. To combat the
ever-evolving threats, adopting advanced models like cybersecurity mesh is necessary to …

Deep learning and federated learning show significant success in cybersecurity for Intrusion
Detection Systems (IDS). This paper presents the Federated Self-Supervised Learning …