Yuhui Zhang

Orcid: 0009-0009-4943-9958

Affiliations:
  • Institute of Information Engineering, Beijing, China


According to our database1, Yuhui Zhang authored at least 11 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Unveiling evasive ransomware and breaking through the predicament: a comprehensive review of evasion techniques and defense mechanisms.
Cybersecur., December, 2026

CryptPEFT: Efficient and Private Neural Network Inference via Parameter-Efficient Fine-Tuning.
Proceedings of the 33rd Annual Network and Distributed System Security Symposium, 2026

SwiftFL: Enabling Speculative Training for On-Device Federated Deep Learning.
Proceedings of the 21st European Conference on Computer Systems, 2026

2025
An Efficient Speculative Federated Tree Learning System With a Lightweight NN-Based Predictor.
IEEE Trans. Parallel Distributed Syst., August, 2025

Exploring the ransomware ecosystem and the active defense concept: Review of attacks and defense.
J. Inf. Secur. Appl., 2025

Comet: Accelerating Private Inference for Large Language Model by Predicting Activation Sparsity.
Proceedings of the IEEE Symposium on Security and Privacy, 2025

ERW-Radar: An Adaptive Detection System against Evasive Ransomware by Contextual Behavior Detection and Fine-grained Content Analysis.
Proceedings of the 32nd Annual Network and Distributed System Security Symposium, 2025

FuzzyHawk: Unveiling Ransomware Behavior Patterns via Graph-Based Fuzzy Matching.
Proceedings of the Information Security and Cryptology - 21st International Conference, 2025

2024
SpecFL: An Efficient Speculative Federated Learning System for Tree-based Model Training.
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2024

2021
ShuffleFL: gradient-preserving federated learning using trusted execution environment.
Proceedings of the CF '21: Computing Frontiers Conference, 2021

2020
Enabling Rack-scale Confidential Computing using Heterogeneous Trusted Execution Environment.
Proceedings of the 2020 IEEE Symposium on Security and Privacy, 2020


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