Critical infrastructure (CI) typically refers to the essential physical and virtual systems, assets,
and services that are vital for the functioning and well-being of a society, economy, or nation …

Cyberspace operations, in conjunction with artificial intelligence and machine learning
enhanced cyberspace infrastructure, make it possible to connect sensors directly to shooters …

Adapting modern approaches for network intrusion detection is becoming critical, given the
rapid technological advancement and adversarial attack rates. Therefore, packet-based …

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 …

Increasingly cyber-attacks are sophisticated and occur rapidly, necessitating the use of
machine learning techniques for detection at machine speed. However, the use of machine …

Large, high quality data sets are essential for training machine learning models to perform
their tasks accurately. The lack of such training data has constrained machine learning …

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

Network Intrusion Detection Systems (NIDS) are an important component of many
organizations' cyber defense, resiliency and assurance strategies. However, one downside …

The number of cyber threats against both wired and wireless computer systems and other
components of the Internet of Things continues to increase annually. In this work, an …

In recent times, the cybersecurity of naval systems has become a major concern; in
particular, there is an increased need for network traffic analysis and detecting the presence …