Yanfeng Qu Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

University of Arkansas at Fayetteville

faculty

4 h-index 15 pubs 43 cited

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Biography and Research Information

OverviewAI-generated summary

Yanfeng Qu's research focuses on enhancing the security and fidelity of industrial and network systems. His work investigates methods for improving industrial network protocol security, particularly through the use of programmable switches. Qu has explored techniques for high-fidelity network emulation, including the development of virtual time systems for container-based environments, which are crucial for I/O intensive applications. His research also addresses the security of cyber-physical systems, with a focus on attack detection and mitigation strategies for critical energy systems. Additionally, Qu has worked on in-network approaches for recovering missing data in synchrophasor measurements, utilizing data plane programmability and deep learning techniques. He has also contributed to pedagogical innovations in online Chinese language course delivery.

Metrics

  • h-index: 4
  • Publications: 15
  • Citations: 43

Selected Publications

  • In-Network Recovery of Delayed and Missing PMU Measurements using Programmable Switches (2025) DOI
  • An In-Network Approach for PMU Missing Data Recovery with Data Plane Programmability (2025) DOI
  • Enhancing P4-Based Network Emulation Fidelity Through a Lightweight Virtual Time System and Application Evaluation (2025) DOI
  • A Deep Learning Approach for In-Network Synchrophasor Missing Data Recovery Using Programmable Network Switches (2024) DOI
  • Leveraging Compact Data Accumulator to Enable In-Network Anomaly Detection in Programmable Switches for Power Grids (2024) DOI
  • Synchronized Power Simulation and Programmable Network Emulation Testbed for SCADA System Security Evaluation (2024) DOI
  • In-Network Logging and Missing Data Recovery In PMU Networks via Programmable Data Plane Devices (2024) DOI
  • Towards Secure and Resilient Synchrophasor Networks Using P4 Programmable Switches (2024) DOI
  • Industrial Network Protocol Security Enhancement Using Programmable Switches (2023) DOI
  • VT-IO: A Virtual Time System Enabling High-Fidelity Container-Based Network Emulation for I/O Intensive Applications (2023) DOI
  • Combining Power Simulation and Programmable Network Emulation for Smart Grid Security Application Evaluation (2023) DOI

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