Dr. Zhuotao Liu is an Associate Professor and Distinguished Researcher at Tsinghua University, where he leads the InspiringGroup. His research centers on secure and efficient networking and systems infrastructure for data transmission and computation, as well as data-centric applications with a strong focus on security and privacy.
Prior to joining Tsinghua, Dr. Liu served as a Technical Lead at Google’s NetInfra (Network Infrastructure) and Google Global Networking (GGN) teams, where he received two “Feats of Engineering” Awards for his contributions to datacenter networking. He is the Principal Investigator of multiple NSFC projects and other national research programs.
Dr. Liu earned his Ph.D. from the University of Illinois at Urbana-Champaign (UIUC) in 2017, supported by the Chiang Chen Overseas Graduate Fellowship. He received his B.S. from Shanghai Jiao Tong University in 2012 and was awarded the National Scholarship for three consecutive years.
Interests
- • Network Security
- • Blockchain Infrastructures and Web3.0 Initiatives
- • Datacenter Networking and Infrastructures
- • Privacy Preserving Machine Learning
- • Agent Security
Education
Publications
(2026).
Blind Gods and Broken Screens: Architecting a Secure, Intent-Centric Mobile Agent Operating System.
(2026).
A Universal Black-Box Evasion Attack against ML-based Malicious Traffic Detection Systems.
NDSS26.
(2026).
Achieving Interpretable DL-based Web Attack Detection through Malicious Payload Localization.
NDSS26.
(2026).
Enhancing Website Fingerprinting Attacks against Traffic Drift.
NDSS26.
(2026).
Understanding the Stealthy BGP Hijacking Risk in the ROV Era.
NDSS26.
(2025).
DiffECN: Differential ECN Marking for Datacenter Networks.
IEEE Transactions on Networking (ToN) 2025.
(2025).
Pegasus: A Universal Framework for Scalable Deep Learning Inference on the Dataplane.
SIGCOMM25.
(2025).
PRED: Performance-oriented Random Early Detection for Consistently Stable Performance in Datacenters.
NSDI25.
(2025).
Revisiting Random Early Detection Tuning for High-Performance Datacenter Networks.
IEEE Transactions on Networking (ToN) 2025.
✨
Distinguished Paper Award Winner
(2025).
TrafficFormer: An Efficient Pre-trained Model for Traffic Data.
S&P25.
(2025).
Training Robust Classifiers for Classfiying Encrypted Traffic under Dynamic Network Conditions.
CCS25.
(2024).
Brain-on-Switch: Towards Advanced Intelligent Network Dataplane via NN-Driven Traffic Analysis at Line-Speed.
NSDI24.
(2024).
CoGNN: Towards Secure and Efficient Collaborative Graph Learning.
CCS24.
(2024).
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach.
Sec24.
(2024).
Detection of Adversarial Attacks via Disentangling Natural Images and Perturbations.
IEEE Transactions on Information Forensics and Security (TIFS) 2024.
(2024).
Effective DDoS Mitigation via ML-Driven In-Network Traffic Shaping.
IEEE Transactions on Dependable and Secure Computing (TDSC) 2024.
✨
Distinguished Paper Award Winner
✨
2024 Internet Defense Prize Winner
(2024).
Low-Quality Training Data Only? A Robust Framework for Detecting Encrypted Malicious Network Traffic.
NDSS24.
(2024).
Pencil: Private and Extensible Collaborative Learning without Non-Colluding Assumption.
NDSS24.
(2024).
Towards Fine-Grained Webpage Fingerprinting at Scale.
CCS24.
✨
Distinguished Paper Award Winner
(2023).
Change Management in Physical Network Lifecycle Automation.
ATC23.
(2023).
Cross Container Attacks: The Bewildered eBPF on Clouds.
Sec23.
(2023).
Learning from Limited Heterogeneous Training Data: Meta-Learning for Unsupervised Zero-day Web Attack Detection across Web Domains.
CCS23.
(2023).
martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable Federated Learning Architecture.
CCS23.
(2023).
Provenance of Training without Training Data: Towards Privacy-Preserving DNN Model Ownership Verification.
WWW23.
(2023).
Robust Multi-tab Website Fingerprinting Attacks in the Wild.
S&P23.
(2023).
Secure Inter-domain Routing and Forwarding via Verifiable Forwarding Commitments.
Arxiv Preprint.
(2023).
Threshold-Based Routing-Topology Co-Design for Optical Data Center.
IEEE/ACM Transactions on Networking (TON) 2023.
(2022).
Automated Multi-Tab Website Fingerprinting Attack.
IEEE Transactions on Dependable and Secure Computing (TDSC) 2022.
(2022).
Dynamic Network Security Function Enforcement via Joint Flow and Function Scheduling.
IEEE Transactions on Information Forensics and Security (TIFS) 2022.
(2022).
FlowTele: Remotely Shaping Traffic on Internet-Scale Networks.
CoNEXT22.
(2022).
Good Learning, Bad Performance: A Novel Attack Against RL-Based Congestion Control Systems.
IEEE Transactions on Information Forensics and Security (TIFS) 2022.
(2022).
Make Web3.0 Connected.
IEEE Transactions on Dependable and Secure Computing (TDSC) 2022.
(2022).
RapidPatch: Firmware Hotpatching for Real-Time Embedded Devices.
Sec22.
(2022).
Unsupervised Contextual Anomaly Detection for Database Systems.
SIGMOD22.
(2021).
Efficient Forwarding Anomaly Detection in Software-Defined Networks.
IEEE Transactions on Parallel and Distributed Systems (TPDS) 2021.
(2019).
DeepIntent: Deep Icon-Behavior Learning for Detecting Intention-Behavior Discrepancy in Mobile Apps.
CCS19.
(2019).
Managing Recurrent Virtual Network Updates in Multi-Tenant Datacenters: A System Perspective.
IEEE Transactions on Parallel and Distributed Systems (TPDS) 2019.
(2019).
Umbrella: Enabling ISPs to Offer Readily Deployable and Privacy-Preserving DDoS Prevention Services.
IEEE Transactions on Information Forensics and Security (TIFS) 2019.
(2018).
Enabling Work-Conserving Bandwidth Guarantees for Multi-Tenant Datacenters via Dynamic Tenant-Queue Binding.
INFOCOM18.
(2018).
Practical Proactive DDoS-Attack Mitigation via Endpoint-Driven In-Network Traffic Control.
IEEE/ACM Transactions on Networking (TON) 2018.