APT (Advanced Persistent Threat) with the characteristics of persistence, stealth, and
diversity is one of the greatest threats against cyber-infrastructure. As a countermeasure …

Query-based black-box attacks have emerged as a significant threat to machine learning
systems, where adversaries can manipulate the input queries to generate adversarial …

Advanced persistent threats (APTs) pose significant challenges for organizations, leading to
data breaches, financial losses, and reputational damage. Existing provenance-based …

As cyber-attacks become increasingly sophisticated and stealthy, it becomes more
imperative and challenging to detect intrusion from normal behaviors. Through fine-grained …

Recent years have witnessed a surge in the growth of Advanced Persistent Threats (APTs),
with significant challenges to the security landscape, affecting industry, governance, and …

The evolution and advancement of cyberattacks pose challenges to existing security
products. Recent concentrated research on provenance graph-based detection has proved …

As Advanced Persistent Threat (APT) complexity increases, provenance data is increasingly
used for detection. Anomaly-based systems are gaining attention due to their attack …

The provenance graph technique has gained popularity for attack analysis, such as
Advanced Persistent Threat (APT) attacks, by creating entity interaction graphs from host …

Enterprises are constantly under attack from sophisticated adversaries. These adversaries
use a variety of techniques to first gain access to the enterprise, then spread laterally inside …

In computer systems, provenance graphs describe causal relationships among operating
system entities (eg, processes, files, and sockets) to represent a system's execution history …