11 citations · 15 across the 28 of their papers we have counts for
7 papers · 1 filter
Guarding Against Malicious Biased Threats (GAMBiT): Experimental Design of Cognitive Sensors and Triggers with Behavioral Impact Analysis
Brandon Beltz, Po-Yu Chen, James Doty +16
This paper introduces GAMBiT (Guarding Against Malicious Biased Threats), a cognitive-informed cyber defense framework that leverages deviations from human rationality as a new def…
Guarding Against Malicious Biased Threats (GAMBiT) Experiments: Revealing Cognitive Bias in Human-Subjects Red-Team Cyber Range Operations
Brandon Beltz, Jim Doty, Yvonne Fonken +9
We present three large-scale human-subjects red-team cyber range datasets from the Guarding Against Malicious Biased Threats (GAMBiT) project. Across Experiments 1-3 (July 2024-Mar…
A Multi-Resolution Dynamic Game Framework for Cross-Echelon Decision-Making in Cyber Warfare
Ya-Ting Yang, Quanyan Zhu
Cyber warfare has become a critical dimension of modern conflict, driven by society's increasing dependence on interconnected digital and physical infrastructure. Effective cyber d…
From Texts to Shields: Convergence of Large Language Models and Cybersecurity
Tao Li, Ya-Ting Yang, Yunian Pan +1
This report explores the convergence of large language models (LLMs) and cybersecurity, synthesizing interdisciplinary insights from network security, artificial intelligence, form…
Symbiotic Game and Foundation Models for Cyber Deception Operations in Strategic Cyber Warfare
Tao Li, Quanyan Zhu
We are currently facing unprecedented cyber warfare with the rapid evolution of tactics, increasing asymmetry of intelligence, and the growing accessibility of hacking tools. In th…
Decision-Dominant Strategic Defense Against Lateral Movement for 5G Zero-Trust Multi-Domain Networks
Tao Li, Yunian Pan, Quanyan Zhu
Multi-domain warfare is a military doctrine that leverages capabilities from different domains, including air, land, sea, space, and cyberspace, to create a highly interconnected b…
A First Order Meta Stackelberg Method for Robust Federated Learning (Technical Report)
Henger Li, Tianyi Xu, Tao Li +3
Recent research efforts indicate that federated learning (FL) systems are vulnerable to a variety of security breaches. While numerous defense strategies have been suggested, they…