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 …

Large language models (LLMs) have strong capabilities in solving diverse natural language
processing tasks. However, the safety and security issues of LLM systems have become the …

Fileless attacks have gained significant prominence and have become the prevailing type of
attack in recent years. The exceptional level of stealthiness and difficulty in detection …

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 …

Cyberattacks are becoming more frequent and sophisticated, and investigating them
becomes more challenging. Provenance graphs are the primary data source to support …

Deep Learning backdoor attacks have a threat model similar to traditional cyber attacks.
Attack forensics, a critical counter-measure for traditional cyber attacks, is hence of …

Today's advanced cyber attack campaigns can often bypass all existing protections. The
primary defense against them is after-the-fact detection, followed by a forensic analysis to …

With the widespread use of Internet of Things (IoT) devices, malware detection has become
a hot spot for both academic and industrial communities. Existing approaches can be …

System auditing is the foundation of attack provenance to investigate root causes and
ramifications of cyber-attacks. However, provenance tracking on coarse-grained audit logs …