activity
20242026
most citedImproving Network Threat Detection by Knowledge Graph, Large Language Model, and Imbalanced Learning

1 citations · 1 across the 6 of their papers we have counts for

collaborators

8 papers

cs.GT2026

LLM Semantic Signaling Game and Mechanism Design: Systematic Blindness, Awareness Shaping, and Mindset Dynamics

Quanyan Zhu

Large language models (LLMs) increasingly mediate strategic interactions through natural language, making semantic control a critical element of communication and deception. This p…

cs.CY2026

Understanding Censorship in Large Language Models: From Mechanisms to Governance

Quanyan Zhu

Large language models (LLMs) increasingly mediate access to information, yet their responses are shaped by training-data curation, alignment procedures, provider policies, inferenc…

cs.CR2025

Agentic AI for Cyber Resilience: A New Security Paradigm and Its System-Theoretic Foundations

Tao Li, Quanyan Zhu

Cybersecurity is being fundamentally reshaped by foundation-model-based artificial intelligence. Large language models now enable autonomous planning, tool orchestration, and strat…

cs.NI2025

Cyber Resilience in Next-Generation Networks: Threat Landscape, Theoretical Foundations, and Design Paradigms

Junaid Farooq, Quanyan Zhu

The evolution of networked systems, driven by innovations in software-defined networking (SDN), network function virtualization (NFV), open radio access networks (O-RAN), and cloud…

cs.CR2025

Game Theory Meets LLM and Agentic AI: Reimagining Cybersecurity for the Age of Intelligent Threats

Quanyan Zhu

Protecting cyberspace requires not only advanced tools but also a shift in how we reason about threats, trust, and autonomy. Traditional cybersecurity methods rely on manual respon…

cs.AI2025

Toward a Dynamic Stackelberg Game-Theoretic Framework for Agentic AI Defense Against LLM Jailbreaking

Zhengye Han, Quanyan Zhu

This paper proposes a game theoretic framework that models the interaction between prompt engineers and large language models (LLMs) as a two player extensive form game coupled wit…