Traditional Intrusion Detection Systems (IDS) cannot cope with the increasing number and
sophistication of cyberattacks such as Advanced Persistent Threats (APT). Due to their high …

Malware poses a severe threat to cyber security. Attackers use malware to achieve their
malicious purposes, such as unauthorized access, stealing confidential data, blackmailing …

Recent years have seen a proliferation of research on adversarial machine learning.
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …

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 …

Provenance graphs are structured audit logs that describe the history of a system's
execution. Recent studies have explored a variety of techniques to analyze provenance …

The success of deep learning (DL) techniques has led to their adoption in many fields,
including attack investigation, which aims to recover the whole attack story from logged …

Advance Persistent Threats (APTs), adopted by most delicate attackers, are becoming
increasing common and pose great threat to various enterprises and institutions. 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 …

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

Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …