Shinan Liu – A Researcher in Networking, Security, and ML Systems

Shinan Liu 刘诗楠

Final-year Ph.D. Candidate

Computer Science, University of Chicago

shinanliu[AT]uchicago[DOT]edu

Google Scholar Page CV (Last updated: Nov. 2024)

I am on the job market for tenure-track faculty positions (2024-2025).
Feel free to get in touch!

Research Statement | Teaching Statement | Diversity Statement

Biography

I am a final-year Ph.D. candidate in the Computer Science Department at the University of Chicago and my advisor is Prof. Nick Feamster. I received my Master of Science degree within Ph.D. at UChicago in 2022, and my Bachelor of Engineering degree from Yingcai Honors College at UESTC, in 2019.

Before coming to UChicago, I was the CEO of a start-up Dominity Security Co., Ltd. I am a Research Intern at Conviva mentored by Prof. Vyas Sekar, and a Research Consultant at LangSafe.ai, and I also had my internship at FedML, Virginia Tech, Qihoo 360, MSRA(short-term visit), KnowWhy, and Tsinghua NISL.

My research lies in the area of Computer Networking and Security, with a focus on developing accessible, reliable, and performant machine learning systems for network data analysis, and employing network data analysis for critical issues in security and privacy. My work often focuses on network traffic analysis, cellular networks, the Internet of Things, and cyber-physical systems. My work has been recognized and published in top conferences and journals such as USENIX Security, SIGMETRICS, CoNext, and UbiComp.

I serve as the head of NSF ACTION AI Institute student advisory council. And I also serve ACM IMC and USENIX NSDI as a PC member and a member of the pre-review task force, and I am also a reviewer of NeurIPS, USENIX ATC, IEEE INFOCOM, IEEE TDSC, IEEE TIFS, IEEE IoTJ, and etc. Additionally, my research has been featured in multiple media outlets, including Forbes, The Wall Street Journal, and ACM TechNews.

Overview of My Research

What’s New?

Excited to be accepted to attend the NeTS Early Career Investigator Workshop 2025 at NSF Headquarters!
I am very grateful for the warmest welcome extended to me by Prof. Brighten Godfrey and Prof. Tianyin Xu at the UIUC SysNet seminar. The community is super kind and insightful!
Immense gratitude to Prof. Zakir Durumeric and Dr. Gerry Wan for hosting my talk at the ESRG of Stanford University! The visit was incredibly welcoming and intellectually enriching.
Glad to be invited as a TPC member of IMC 2024!
Our recent work on the highly efficient ML-based traffic analysis system ServeFlow: A Fast-Slow Model Architecture for Network Traffic Analysis is now on arXiv! So are CATO and AC-DC.
Recently, I had the privilege of giving a talk on “Operational ML in Networking” at both Carnegie Mellon University and Emerald Inc., extending my sincere thanks to Prof. Peter Steenkiste and Prof. Srinivasan Seshan at CMU, and Prof. Dina Katabi at MIT for their gracious invitations.
How to generate high-fidelity PCAP traces using a Generative Model? Our latest work “Generative, High-Fidelity Network Traces” explores this question and has just been accepted by HotNets’23. Our full paper NetDiffusion: Network Data Augmentation Through Protocol-Constrained Traffic Generation has been accepted by SIGMETRICS’24. Huge thanks to Chase, Aaron, Arjun, Paul, Francesco, and Nick for making it happen!
Started to serve as the Head of the Student Advisory Council at the ACTION AI Institute.
Our paper “LEAF: Navigating Concept Drift in Cellular Networks” has been accepted by CoNext’23! It is the first end-to-end work to characterize, explain, and mitigate concept drift in networking. Huge shout out to Francesco, Paul, Arjun, Nick, and our Verizon collaborators Hector, Tim, and Brian!!
We got our paper “AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environment” accepted at UbiComp/IMWUT 2023. Shout out to Tarun, Ted, Jinjin, John, Sanjay, and Nick! Check out our website for released datasets, processed features, models, and analysis pipelines.

Selected Manuscripts

[1] ServeFlow: A Fast-Slow Model Architecture for Network Traffic Analysis [arXiv]

Shinan Liu, Ted Shaowang, Gerry Wan, Jeewon Chae, Jonatas Marques, Sanjay Krishnan, Nick Feamster (In Submission）

[2] AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments [paper] [website] [data] [pipeline] [model] [blog]

Shinan Liu, Tarun Mangla, Ted Shaowang, Jinjin Zhao, John Paparrizos, Sanjay Krishnan, Nick Feamster Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (UbiComp/IMWUT’23), October 2023

[3] LEAF: Navigating Concept Drift in Cellular Networks [paper] [data]

Shinan Liu, Francesco Bronzino, Paul Schmitt, Arjun Nitin Bhagoji, Nick Feamster, Hector Garcia Crespo, Timothy Coyle, Brian Ward. The 19th International Conference on emerging Networking EXperiments and Technologies（CoNext’23）, December 2023

[4] Stars Can Tell: A Robust Method to Defend against GPS Spoofing Attacks Using Off-the-shelf Chipset [paper] [website] [data] [apk release]

Shinan Liu*, Xiang Cheng*, Hanchao Yang, Yuanchao Shu, Xiaoran Weng, Ping Guo, Kexiong (Curtis) Zeng, Gang Wang, Yaling Yang. 30th USENIX Security Symposium（USENIX Security’21）, August 2021

[5] NetDiffusion: Network Data Augmentation Through Protocol-Constrained Traffic Generation [paper] [blog] [code]

Xi Jiang, Shinan Liu, Aaron Gember-Jacobson, Arjun Nitin Bhagoji, Paul Schmitt, Francesco Bronzino, Nick Feamster. ACM SIGMETRICS / IFIP PERFORMANCE 2024（SIGMTRICS’24), June. 2024

[6] All Your GPS Are Belong To Us: Towards Stealthy Manipulation of Road Navigation Systems [paper] [demo][media coverages]

Kexiong (Curtis) Zeng, Shinan Liu, Yuanchao Shu, Dong Wang, Haoyu Li, Yanzhi Dou, Gang Wang and Yaling Yang. 27th USENIX Security Symposium（USENIX Security’18）, August 2018