14 citations · 25 across the 26 of their papers we have counts for
14 papers · 1 filter
DEFENGRAPH: Knowledge Graph-Enhanced LLMs for Blue Team Cyber Defense
Zhen Wang, Kristen Moore, Qin Wang +7
Large Language Models (LLMs) show promise for supporting decision-making in cybersecurity, but their reliability in high-stakes, time-evolving environments remains limited due to h…
AgenticVM: Agentic AI for Adaptive Software Vulnerability Management
Asrul Arifin, Hussain Ahmad, Yiyao Zhang +1
As software systems grow in scale and complexity, vulnerability management is increasingly strained by high alert volumes, fragmented toolchains, and manual triage processes. We in…
Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning
Yiyao Zhang, Diksha Goel, Hussain Ahmad
Autonomous agents are increasingly deployed in both offensive and defensive cyber operations, creating high-speed, closed-loop interactions in critical infrastructure environments.…
TempoNet: Learning Realistic Communication and Timing Patterns for Network Traffic Simulation
Kristen Moore, Diksha Goel, Cody James Christopher +5
Realistic network traffic simulation is critical for evaluating intrusion detection systems, stress-testing network protocols, and constructing high-fidelity environments for cyber…
From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Alsharif Abuadbba, Chris Hicks, Kristen Moore +4
Large Language Models (LLMs) are set to reshape cybersecurity by augmenting red and blue team operations. Red teams can exploit LLMs to plan attacks, craft phishing content, simula…
Co-Evolutionary Defence of Active Directory Attack Graphs via GNN-Approximated Dynamic Programming
Diksha Goel, Hussain Ahmad, Kristen Moore +1
Modern enterprise networks increasingly rely on Active Directory (AD) for identity and access management. However, this centralization exposes a single point of failure, allowing a…