Qiao Zhang

Orcid: 0000-0002-7752-0528

Affiliations:
  • Old Dominion University, School of Cybersecurity, Norfolk, VA, USA (PhD 2021)


According to our database1, Qiao Zhang authored at least 18 papers between 2018 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Contrast-Then-Approximate: Analyzing Keyword Leakage of Generative Language Models.
IEEE Trans. Inf. Forensics Secur., 2024

Comet: A Communication-efficient and Performant Approximation for Private Transformer Inference.
CoRR, 2024

From Individual Computation to Allied Optimization: Remodeling Privacy-Preserving Neural Inference with Function Input Tuning.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

SPOT: Structure Patching and Overlap Tweaking for Effective Pipelining in Privacy-Preserving MLaaS with Tiny Clients.
Proceedings of the 44th IEEE International Conference on Distributed Computing Systems, 2024

MOSAIC: A Prune-and-Assemble Approach for Efficient Model Pruning in Privacy-Preserving Deep Learning.
Proceedings of the 19th ACM Asia Conference on Computer and Communications Security, 2024

United We Stand: Accelerating Privacy-Preserving Neural Inference by Conjunctive Optimization with Interleaved Nexus.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Privacy-Preserving Machine Learning as a Service: Challenges and Opportunities.
IEEE Netw., November, 2023

PRISC: Privacy-Preserved Pandemic Infection Risk Computation Through Cellular-Enabled IoT Devices.
IEEE Internet Things J., September, 2023

2022
SecureTrain: An Approximation-Free and Computationally Efficient Framework for Privacy-Preserved Neural Network Training.
IEEE Trans. Netw. Sci. Eng., 2022

DT-SSIM: A Decentralized Trustworthy Self-Sovereign Identity Management Framework.
IEEE Internet Things J., 2022

Joint Linear and Nonlinear Computation across Functions for Efficient Privacy-Preserving Neural Network Inference.
CoRR, 2022

Hunter: HE-Friendly Structured Pruning for Efficient Privacy-Preserving Deep Learning.
Proceedings of the ASIA CCS '22: ACM Asia Conference on Computer and Communications Security, Nagasaki, Japan, 30 May 2022, 2022

2021
Joint Linear and Nonlinear Computation with Data Encryption for Efficient Privacy-Preserving Deep Learning.
PhD thesis, 2021

Privacy-Preserving Deep Learning Based on Multiparty Secure Computation: A Survey.
IEEE Internet Things J., 2021

GALA: Greedy ComputAtion for Linear Algebra in Privacy-Preserved Neural Networks.
Proceedings of the 28th Annual Network and Distributed System Security Symposium, 2021

2019
CHEETAH: An Ultra-Fast, Approximation-Free, and Privacy-Preserved Neural Network Framework based on Joint Obscure Linear and Nonlinear Computations.
CoRR, 2019

2018
GELU-Net: A Globally Encrypted, Locally Unencrypted Deep Neural Network for Privacy-Preserved Learning.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Marvel: Mann-Whitney Rank-Sum Testing via Segments Labeling for Indoor Pedestrian Localization.
Proceedings of the 2018 IEEE International Conference on Communications, 2018


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