Meng Hao

Orcid: 0000-0002-1545-1926

Affiliations:

Singapore Management University, School of Computing and Information Systems, Singapore
University of Electronic Science and Technology of China, Chengdu, China (PhD 2024)

According to our database¹, Meng Hao authored at least 51 papers between 2019 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

Efficient Fuzzy Private Set Intersection from Secret-shared OPRF.

[BibT_eX]

[DOI]

CoRR, April, 2026

Delayed Backdoor Attacks: Exploring the Temporal Dimension as a New Attack Surface in Pre-Trained Models.

[BibT_eX]

[DOI]

CoRR, March, 2026

PrivTF: Efficient and Privacy-Preserving Transformer Inference With Optimized Protocols for Secure NLP.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Sci. Eng., 2026

T<sup>3</sup>AT: Threshold-Authorized, Threshold-Redeemable, and Non-Transferable Anonymous Tokens.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Forensics Secur., 2026

Conan: Secure and Reliable Machine Learning Inference Against Malicious Service Providers.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Forensics Secur., 2026

Sanitizer: Blazing-Fast, Private, and Robust Federated Learning.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Forensics Secur., 2026

HyperSiniel: Guaranteed Output Delivery Comes (Almost) Free in Private Delegation of zkSNARKs.

[BibT_eX]

[DOI]

IEEE Trans. Dependable Secur. Comput., 2026

An Advanced Gradient Leakage Attack Against Duplicate Labels via Model Outputs Reconstruction.

[BibT_eX]

[DOI]

IEEE Trans. Dependable Secur. Comput., 2026

Online-Friendly Robust Threshold ECDSA with Constant Amortized Communication.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2026

Scalable Honest-majority MPC for Machine Learning from Mixed Secret Sharings.

[BibT_eX]

[DOI]

Meilin Li

Meng Hao

Yu Chen

IACR Cryptol. ePrint Arch., 2026

2025

BadTime: An Effective Backdoor Attack on Multivariate Long-Term Time Series Forecasting.

[BibT_eX]

[DOI]

CoRR, August, 2025

The Gradient Puppeteer: Adversarial Domination in Gradient Leakage Attacks through Model Poisoning.

[BibT_eX]

[DOI]

CoRR, February, 2025

Charge Your Clients: Payable Secure Computation and Its Applications.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Forensics Secur., 2025

The Gradient Puppeteer: Adversarial Domination in Gradient Leakage Attacks Through Model Poisoning.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Forensics Secur., 2025

Practical Keyword Private Information Retrieval from Key-to-Index Mappings.

[BibT_eX]

[DOI]

Proceedings of the 34th USENIX Security Symposium, 2025

Distributed Function Secret Sharing and Applications.

[BibT_eX]

[DOI]

Proceedings of the 32nd Annual Network and Distributed System Security Symposium, 2025

SecInfer: Secure and Efficient Model Inference on Vertically Partitioned Data.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2025

2024

Vertical Federated Learning Across Heterogeneous Regions for Industry 4.0.

[BibT_eX]

[DOI]

IEEE Trans. Ind. Informatics, August, 2024

SVFGNN: A privacy-preserving vertical federated graph neural network model training framework based on split learning.

[BibT_eX]

[DOI]

Yanjun Liu

Hongwei Li

Meng Hao

Peer Peer Netw. Appl., January, 2024

Efficient and Privacy-Preserving Outsourcing of Gradient Boosting Decision Tree Inference.

[BibT_eX]

[DOI]

IEEE Trans. Serv. Comput., 2024

Stealthy Targeted Backdoor Attacks Against Image Captioning.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Forensics Secur., 2024

SecBNN: Efficient Secure Inference on Binary Neural Networks.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Forensics Secur., 2024

Decentralized Multi-Client Functional Encryption for Inner Product With Applications to Federated Learning.

[BibT_eX]

[DOI]

IEEE Trans. Dependable Secur. Comput., 2024

Combinational Backdoor Attack against Customized Text-to-Image Models.

[BibT_eX]

[DOI]

CoRR, 2024

Unbalanced Circuit-PSI from Oblivious Key-Value Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 33rd USENIX Security Symposium, 2024

Scalable Zero-knowledge Proofs for Non-linear Functions in Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the 33rd USENIX Security Symposium, 2024

Benchmark GELU in Secure Multi-Party Computation.

[BibT_eX]

[DOI]

Proceedings of the 2024 IEEE Global Communications Conference, 2024

Unbalanced Private Set Union with Reduced Computation and Communication.

[BibT_eX]

[DOI]

Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024

2023

ESA-FedGNN: Efficient secure aggregation for federated graph neural networks.

[BibT_eX]

[DOI]

Peer Peer Netw. Appl., March, 2023

FastSecNet: An Efficient Cryptographic Framework for Private Neural Network Inference.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Forensics Secur., 2023

PriVDT: An Efficient Two-Party Cryptographic Framework for Vertical Decision Trees.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Forensics Secur., 2023

Extracting Cloud-based Model with Prior Knowledge.

[BibT_eX]

[DOI]

CoRR, 2023

GuardHFL: Privacy Guardian for Heterogeneous Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Toward Efficient and End-to-End Privacy-Preserving Distributed Gradient Boosting Decision Trees.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

TriFSS: Secure Trigonometric Function Evaluation via Function Secret Sharing.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

SecMath: An Efficient 2-Party Cryptographic Framework for Math Functions.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

Membership Inference Attacks Against the Graph Classification.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2023

Practical and Privacy-Preserving Density-Based Clustering via Shuffling.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2023

Privacy-Preserving and Verifiable Outsourcing Inference Against Malicious Servers.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2023

2022

Practical Membership Inference Attack Against Collaborative Inference in Industrial IoT.

[BibT_eX]

[DOI]

IEEE Trans. Ind. Informatics, 2022

Iron: Private Inference on Transformers.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Secure Feature Selection for Vertical Federated Learning in eHealth Systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2022

Efficient and Privacy-Preserving Federated Learning with Irregular Users.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2022

CryptoFE: Practical and Privacy-Preserving Federated Learning via Functional Encryption.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2022

Fast Secure Aggregation for Privacy-Preserving Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2022

2021

Enhanced Mixup Training: a Defense Method Against Membership Inference Attack.

[BibT_eX]

[DOI]

Proceedings of the Information Security Practice and Experience: 16th International Conference, 2021

Towards Lightweight and Efficient Distributed Intrusion Detection Framework.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2021

Efficient, Private and Robust Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the ACSAC '21: Annual Computer Security Applications Conference, Virtual Event, USA, December 6, 2021

2020

Efficient and Privacy-Enhanced Federated Learning for Industrial Artificial Intelligence.

[BibT_eX]

[DOI]

IEEE Trans. Ind. Informatics, 2020

Privacy-aware and Resource-saving Collaborative Learning for Healthcare in Cloud Computing.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Communications, 2020

2019

Towards Efficient and Privacy-Preserving Federated Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Communications, 2019

Meng Hao

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