Welcome to the InspiringGroup

The InspiringGroup is a dynamic research group here @ Tsinghua University INSC. We have worked on a wide range of topics centering around data. We build secure and efficient underlying systems infrastructure to support data communications. Meanwhile, we create various data-centric applications with special interests on data security and privacy. See our Research for more details.

The InspiringGroup is led by Principal Investigator (PI), Dr. Zhuotao Liu, who has a strong track-record in both academia and industry. Dr. Liu received his Ph.D. from University of Illinois at Urbana-Champaign (UIUC) and worked at Google as a Technical Lead in both the NetInfra (Network Infrastructure) and GGN (Google Global Networking) team.

We are looking for new Ph.D. students, Postdocs, Master students, undergraduate students and external interns to join our team. Here at InspiringGroup, we strive to build a friendly, supportive, and flourishing culture, and to make your experiences at InspiringGroup full of “Wow Moments”. See Future Students.


January 2022

[Network Security] Two works accepted by IEEE TIFS'22, on Network Virtual Functions and Learning-based Congestion Control, respectively.

December 2021

[Systems Security] Our work on detecting anomaly accesses to database systems is accepted by ACM SIGMOD'22.

October 2021

[Privacy Computing] Our work on performing practical differentially private online advertising is accepted by Computers & Security 2021.

October 2021

[Systems Security] Our work on hot-patching IoT devices to fix vulnerabilities based on eBPF is accepted by USENIX Security'22.

September 2021

[Systems Security] Our work on detecting malicious accounts in WeChat is accepted by ACSAC'21.

September 2021

[New Members] Served in the Technical Interview Committee for graduate student admission in Department of Computer Science and Institute of Cyberspace. Congrats to all new coming graudates of class 2022. Welcome Jinzhu and Xuanqi to join my group.

August 2021

[Systems Security] Our work on investigating Advanced Persistent Threat (APT) via causality analysis is accepted by USENIX Security'22. Source code is released.

August 2021

[ML Security] Our work on security of Graph Neural Networks is accepted by ACM CCS'21. Source code is released.

July 2021

[Privacy Computing] Our work on de-anonymizing encrypted networking traffic is accepted by IEEE TDSC'21.

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