Zhonghao Liao, Ph.D.

Assistant Professor Milwaukee School of Engineering

  • Milwaukee WI

Zhonghao Liao has expertise in the areas of cybersecurity and distributed systems.

Contact

Milwaukee School of Engineering

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Education, Licensure and Certification

Ph.D.

Computer Engineering

Iowa State University

2024

M.S.

Computer Engineering

Iowa State University

2022

B.E.

Automation

Jilin University, China

2014

Biography

Dr. Zhonghao Liao is an Assistant Professor in the Department of Computer Science and Software Engineering at MSOE. He received his Ph.D. in computer science from Iowa State University in 2024. He is passionate about teaching and research, and his research interests include security and privacy, distributed systems, and blockchain.

Areas of Expertise

Digital Forensics
Data-Driven Security and Privacy
Verifiable Computing
Blockchain
Distributed System
Applied cryptography
Accountability and Anonymity
Hardware Security

Accomplishments

Professional Advancement Grants

2021

Iowa State University

Graduate Student Professional Development Support

2021

Iowa State University

Research Excellence Award

2024

Iowa State University

Social

Selected Publications

AgBIS: A Blockchain-enabled Crop Insurance Platform Against Adverse Selection, Moral Hazard, and Insurance Frauds

2023 IEEE International Conference on Blockchain (Blockchain)

2023

Crop insurance is widely adopted to help farmers stabilize incomes and mitigate uncertainties. However, current crop insurance systems face significant challenges, including adverse selection, moral hazard, and insurance frauds, further exacerbating the difficulties associated with cost, program sustainability, and market failures.

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RUDBA: Reusable User-Device Biometric Authentication Scheme for Multi-service Systems

2021 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)

2021

The authentication and verification of user and device identities require cost-effective solutions. Two emerging approaches, biometric authentication and devices’ fingerprint, allow users and devices to prove their identity efficiently and securely. Furthermore, users are inclined to register multiple services with the same secret information.

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The Cell Dependency Analysis on Learning SRAM Power-Up States

2018 Asian Hardware Oriented Security and Trust Symposium (AsianHOST)

2018

The authentication and verification of a device requires strong and cost-effective digital fingerprint based solutions. The power-up state of Static Random Access Memory (SRAMs) has been widely used for a variety of authentication and identification purposes, such as SRAM-based Physical Unclonable Functions (PUFs) and Random Number Generators (RNGs), which form the basis for many cryptographic algorithms and protocols.

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