7 citations · 13 across the 9 of their papers we have counts for
7 papers · 1 filter
NeuroGraph: An AI Graph-Driven Neuro-Symbolic Framework for Explainable Threat Reasoning in Advanced Manufacturing
Padmeswari Nandiya, Ahmad Mohsin, Ahmed Ibrahim +2
The growing complexity of cyber-physical attack surfaces in advanced manufacturing has made cyber threat intelligence analysis increasingly difficult. Although large language model…
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…
Enhancing Adversarial Robustness in Network Intrusion Detection: A Layer-wise Adaptive Regularization Approach
Hira Nasir, Eiman Javed, Balawal Shabir +2
The new wave of adversarial attacks that utilize gradient-related vulnerabilities in neural network-based classifiers makes Network Intrusion Detection Systems more open to such th…
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…
BRIDG-ICS: AI-Grounded Knowledge Graphs for Intelligent Threat Analytics in Industry~5.0 Cyber-Physical Systems
Padmeswari Nandiya, Ahmad Mohsin, Ahmed Ibrahim +2
Industry 5.0's increasing integration of IT and OT systems is transforming industrial operations but also expanding the cyber-physical attack surface. Industrial Control Systems (I…
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…
Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs
Ahmad Mohsin, Helge Janicke, Adrian Wood +3
Large Language Models (LLMs) such as ChatGPT and GitHub Copilot have revolutionized automated code generation in software engineering. However, as these models are increasingly uti…