Cybersecurity knowledge graphs, which represent cyber-knowledge with a graph-based
data model, provide holistic approaches for processing massive volumes of complex …

The development of key technologies of knowledge graph (KG) has promoted the
development of machine cognition technology, and the combination of KG and industry as …

Cyber-defense systems are being developed to automatically ingest Cyber Threat
Intelligence (CTI) that contains semi-structured data and/or text to populate knowledge …

Generative Artificial Intelligence (GenAI) has emerged as a powerful technology capable of
autonomously producing highly realistic content in various domains, such as text, images …

Storytelling, and the delivery of societal narratives, enable human beings to communicate,
connect, and understand one another and the world around them. Narratives can be defined …

Today there is a significant amount of fake cybersecurity related intelligence on the internet.
To filter out such information, we build a system to capture the provenance information and …

Machine Learning has increased our ability to model large quantities of data efficiently in a
short time. Machine learning approaches in many application domains require collecting …

Cyber defense exercises are an important avenue to understand the technical capacity of
organizations when faced with cyber-threats. Information derived from these exercises often …

Neurosymbolic artificial intelligence (AI) is an emerging and quickly advancing field that
combines the subsymbolic strengths of (deep) neural networks and the explicit, symbolic …

In recent years, cyber attacks have shown diversified, purposeful, and organized
characteristics, which pose significant challenges to cyber defense decision-making on …