Shinan Liu – Becoming a Hacker and Researcher

Shinan Liu 刘诗楠

5th Year Ph.D. Student

Computer Science, University of Chicago

shinanliu[AT]uchicago[DOT]edu

Biography

I am a 5th year Ph.D. student in the Computer Science Department at the University of Chicago and my advisor is Prof. Nick Feamster. And I received my Master of Science degree within Ph.D. at UChicago in the Summer of 2022 and my Bachelor of Engineering degree from Yingcai Honors College at UESTC.

Before coming to UChicago, I was the CEO of a start-up Dominity Security Co., Ltd. I also had my internship at FedML, Virginia Tech, Qihoo 360, MSRA(short-term visit), KnowWhy, Tsinghua NISL.

My research interests lie in the intersection between ML systems, networking, security & privacy, and measurement. Typical scenarios I’ve explored include Cellular Networks, IoT, and CPS. My dream and what I constantly endeavor is to become a researcher, hacker, poet, and practical idealist.

What’s new?

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. Check out the preprint of our full paper NetDiffusion: Network Data Augmentation Through Protocol-Constrained Traffic Generation!
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 get 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.
Thanks to the invitation from Prof. Wenke Lee, I shared my research “Towards Data-centric AI for Robust and Secure Operations in Networks” at GaTech. Really glad to have the opportunity to talk to the great minds at GaTech!
Our paper “Stars can tell: A Robust Method to Defend against GPS Spoofing Attacks Using Off-the-shelf Chipset“ is accepted and will appear at USENIX Security 2021. We released the website, smartphone prototype, and dataset! Shout out to Xiang, Hanchao, Yuanchao, Xiaoran, Ping, Curtis, Prof. Wang, and Prof. Yang!

Selected Manuscripts

ML for Networking

[1] 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

[2] 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

Network Security

[3] 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

[4] 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