5 papers
Unveiling the Black Box: A Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agents
Diksha Goel, Kristen Moore, Jeff Wang +2
Reinforcement Learning (RL) agents are increasingly used to simulate sophisticated cyberattacks, but their decision-making processes remain opaque, hindering trust, debugging, and…
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…
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…
CyberAlly: Leveraging LLMs and Knowledge Graphs to Empower Cyber Defenders
Minjune Kim, Jeff Wang, Kristen Moore +7
The increasing frequency and sophistication of cyberattacks demand innovative approaches to strengthen defense capabilities. Training on live infrastructure poses significant risks…
CAMP in the Odyssey: Provably Robust Reinforcement Learning with Certified Radius Maximization
Derui Wang, Kristen Moore, Diksha Goel +8
Deep reinforcement learning (DRL) has gained widespread adoption in control and decision-making tasks due to its strong performance in dynamic environments. However, DRL agents are…