Guoxing Chen
Also known as 陈国兴
Guoxing Chen is a computer security researcher at Shanghai Jiao Tong University whose work on trusted execution environments extends to the security of machine-learning models. He earned bachelor's and master's degrees at SJTU in 2010 and 2013 and a PhD at the Ohio State University in 2019. At Ohio State he coauthored the SgxPectre attacks on Intel SGX enclaves, and he worked as a research scientist at Facebook before joining the SJTU faculty in 2021. His later papers include a 2022 method for fingerprinting stolen deep neural networks and 2025 studies of trojaned LLM adapters and of inverting LLM internal states. He is a tenure-track associate professor in SJTU's School of Computer Science and a member of its Institute of Artificial Intelligence and Cognitive Security.
Timeline
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2010–2019
Degrees from SJTU and Ohio State
He earns a bachelor's degree at Shanghai Jiao Tong University in 2010 and a master's degree there in 2013. He completes a PhD at the Ohio State University in 2019, advised by Ten H. Lai, Dong Xuan and Yinqian Zhang.
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2018
HyperRace for SGX enclaves
In 2018, he coauthors "Racing in Hyperspace" at the IEEE Symposium on Security and Privacy. The paper presents HyperRace, an LLVM-based tool that instruments SGX enclave programs, creates a shadow thread for each enclave thread and asks the operating system to place both on the same physical core, which closes Hyper-Threading side channels.
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2018–2020
The SgxPectre attacks
In 2018, while at Ohio State, he posts SgxPectre on arXiv with Sanchuan Chen, Yuan Xiao, Yinqian Zhang, Zhiqiang Lin and Ten H. Lai. The attacks use speculative execution to steal seal keys and attestation keys from Intel signed quoting enclaves. The work appears at IEEE EuroS&P in 2019 and in IEEE Security & Privacy in 2020.
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2019–2021
Research scientist at Facebook
He works as a research scientist at Facebook from 2019 until he moves to Shanghai Jiao Tong University in March 2021.
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2021–2024
Assistant professor at SJTU
In March 2021, he joins SJTU's School of Computer Science, where he is a tenure-track assistant professor through 2024.
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2022
Fingerprinting stolen neural networks
In 2022, he coauthors a CVPR oral paper on fingerprinting deep neural networks with universal adversarial perturbations. The method lets a service provider verify whether a suspect model was stolen through model extraction attacks, detecting model IP breaches with confidence above 99.99 within 20 fingerprints.
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2025
Trojan adapters and prompt inversion
In 2025, he coauthors two papers on attacks against large language models. "The Philosopher's Stone" at NDSS shows that an infected low-rank adapter can make an LLM output adversary-defined content on specific triggers, and "Depth Gives a False Sense of Privacy" at USENIX Security shows that LLM internal states can be inverted to recover input prompts, including a 4,112-token medical consulting prompt.
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Since 2025
Associate professor at SJTU
In 2025, he becomes a tenure-track associate professor at SJTU's School of Computer Science, where he is a member of the Institute of Artificial Intelligence and Cognitive Security. His team takes students in system security, hardware security, side channels, data privacy and trusted execution environments.
Career
- Since 2021Shanghai Jiao Tong UniversityAssistant professor, Associate professor
- 2019–2021MetaResearch scientist
Education
- 2019Ohio State UniversityPhD
- 2013Shanghai Jiao Tong UniversityMaster's degree
- 2010Shanghai Jiao Tong UniversityBachelor's degree
Sources and credits
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- Guoxing Chen's Homepage
- Guoxing Chen-上海交通大学计算机学院(网络空间安全学院、密码学院)
- Racing in Hyperspace: Closing Hyper-Threading Side Channels on SGX with Contrived Data Races | NSF Public Access Repository
- SgxPectre Attacks: Stealing Intel Secrets from SGX Enclaves via Speculative Execution
- Spectre haunts Intel's SGX defense: CPU flaws can be exploited to snoop on enclaves
- Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations
- The Philosopher's Stone: Trojaning Plugins of Large Language Models
- Depth Gives a False Sense of Privacy: LLM Internal States Inversion | USENIX
- Institute of Artificial Intelligence and Cognitive Security-上海交通大学计算机学院(网络空间安全学院、密码学院)