Research

My works focus on uncovering previously unexplored vulnerabilities in state-of-the-art networking and AI systems from a red-team perspective, and subsequently proposing effective defense mechanisms to strengthen their security and resilience.

Here are a few selected projects from my PhD research.

Model Inversion Attacks against Secure Federated Learning Systems

Building Trustworthy and Verifiable Spectrum Sharing Systems

Protecting Network Timing from Byzantine Attacks within Time-Sensitive IoT Networks

Beyond these areas, I am also interested in a range of network and information security topics such as Blockchain, autonomous vehicle security, federated learning model poisoning attacks, model fingerprinting, and intrusion detection systems.