Communication protocols form the bedrock of our interconnected world, yet vulnerabilities
within their implementations pose significant security threats. Recent developments have …

System auditing provides a low-level view into cyber threats by monitoring system entity
interactions. In response to advanced cyber-attacks, one prevalent solution is to apply data …

Auditing, a central pillar of operating system security, has only recently come into its own as
an active area of public research. This resurgent interest is due in large part to the notion of …

Software logging is the practice of recording different events and activities that occur within a
software system, which are useful for different activities such as failure prediction and …

In adversarial machine learning, new defenses against attacks on deep learning systems
are routinely broken soon after their release by more powerful attacks. In this context …

While deep learning (DL) has emerged as a powerful technique, its benefits must be
carefully considered in relation to computational costs. Specifically, although DL methods …

We present PROVNINJA, a framework designed to generate adversarial attacks that aim to
elude provenance-based Machine Learning (ML) security detectors. PROVNINJA is …

We present ProvG-Searcher, a novel approach for detecting known APT behaviors within
system security logs. Our approach leverages provenance graphs, a comprehensive graph …

Artificial Intelligence (AI) has achieved significant advancements in technology and research
with the development over several decades, and is widely used in many areas including …

Advanced Persistent Threats (APT) attacks have plagued modern enterprises, causing
significant financial losses. To counter these attacks, researchers propose techniques that …