The exponential growth of the internet and inter-connectivity has resulted in an extensive
increase in network size and the corresponding data, which has led to numerous novel …

In the dynamic field of the Industrial Internet of Things (IIoT), the networks are increasingly
vulnerable to a diverse range of cyberattacks. This vulnerability necessitates the …

Deep learning has enabled network intrusion detection rates as high as 99.9% for malicious
network packets without requiring feature engineering. Adversarial machine learning …

Intrusion detection systems, also known as IDSs, are widely regarded as one of the most
essential components of an organization's network security. This is because IDSs serve as …

Recent advancements in artificial intelligence (AI) and machine learning (ML) algorithms,
coupled with the availability of faster computing infrastructure, have enhanced the security …

Ensuring the security and integrity of computer and network systems is of utmost importance
in today's digital landscape. Network intrusion detection systems (NIDS) play a critical role in …

Cyber threats are moving beyond human comprehension and reaction capability in a rapidly
evolving world. Deep learning models for network intrusion detection are becoming …

Analyzing network traffic activities is imperative in network security to detect attack patterns.
Due to the complex nature of network traffic event activities caused by continuously …

User intents are ever-changing, which requires deep learning models to have the ability to
classify unknown intents. Meta-learning aims to solve this problem by improving the model's …

The vacuum switch uses vacuum as the insulation and arc-extinguishing medium. It is the
core equipment in high-voltage transmission and distribution power systems. Online …