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Short Bio

Dr. Yuan Hong is an Assistant Professor of Computer Science at Illinois Institute of Technology since 2017. He jointly establishes and directs the new Cybersecurity program at Illinois Tech. He received the NSF CAREER Award in 2021. Prior to joining IIT, he was an Assistant Professor at SUNY-Albany and one of the founding faculty members of the Digital Forensics and Cybersecurity programs. He received his Ph.D degree from Rutgers University in 2014. He received a National Physics Olympiad prize in China.

He is broadly interested in Data Privacy (e.g., differential privacy, secure multiparty computation, and TEE), AI Security (e.g., adversarial learning, and certified defenses), Mechanism Design and Optimization. He regularly publishes papers in top venus in Security and Data Science, including Oakland, CCS, PETS, TDSC, TIFS, TOPS, EMNLP, AAMAS, CIKM, EDBT, ICDM, ICDCS and TKDE, as well as interdisciplinary venues (Engineering/Math/IS) such as TEM, T-ITS, TMIS, Operational Research, and Optimization Letters. He is a Senior Member of the IEEE (2018), and his research is supported by the NSF, AFOSR, WISER, and POP.

Multiple Funded Ph.D. positions are open for Spring 2022 and Fall 2022 in our DataSec Lab. Please email your application materials to Dr. Yuan Hong if you are interested in data privacy and/or AI security research.


  • [08/2021] A paper on attacking the privacy of instance encoding for language understanding is accepted to EMNLP'21. Congrats, Shangyu
  • [07/2021] Our project "Privately Collecting and Analyzing V2X Data for Urban Traffic Modeling" (Lead PI: Yuan) is funded by the NSF SaTC Core Program (very grateful to NSF SaTC for the generous support)
  • [07/2021] A paper on attacking video recognition systems with universal 3-D perturbations is accepted to Oakland'22 (Acceptance Rate: 15.1%). Congrats, Shangyu and Han
  • [Recent TPC] PETS'21, AAAI'21, DASFAA'21, AAMAS'21, CCGRID'21, CVPR'21, ICCV'21, ICLR-DPML'21, DBSEC'21, TPS'21, PETS'22, AAAI'22 (SPC), AAMAS'22, CVPR'22
  • [05/2021] Yuan will teach CS528 Data Privacy and Security in Fall 2021
  • [04/2021] A paper on privacy and utility preserving data outsourcing (generalized framework for a variety of datasets) is accepted to TKDE. Congrats, Shangyu, Meisam and Han
  • [04/2021] Shangyu will be an Applied Scientist Intern at Amazon Research in Summer 2021. Congrats, Shangyu
  • [04/2021] A poster paper on TEE-Blockchain for Auction is accepted to ICDCS'21. Congrats, Bingyu
  • [03/2021] Yuan receives the NSF CAREER Award (very grateful to NSF SaTC for the generous support) [University News]
  • [01/2021] A paper on privacy preserving cloud-based DNN inference is accepted to ICASSP'21. Congrats, Shangyu and Bingyu
  • [11/2020] A paper on multi-view approach to anonymizing network traces is accepted to TOPS (formerly TISSEC). Congrats, Meisam
  • [11/2020] Congratuations to Dr. Meisam Mohammady on sucessfully defending his Ph.D. dissertation (Won the Distinguished Doctoral Thesis Prize), and he will work as a Research Scientist at Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia
  • [10/2020] Yuan will teach CS549 Cryptography in Spring 2021
  • [08/2020] A paper on attacking system log parsers is accepted to CIKM'20 (Acceptance Rate: 25.9%). Congrats, Jingyu and Bingyu
  • [06/2020] A paper on optimizing the randomization for differential privacy is accepted to CCS'20 (Acceptance Rate: 16.9%). Congrats, Meisam and Shangyu
  • [06/2020] A paper on identifying visual privacy attributes (ML for Privacy) is accepted to ICPR'20. Congrats, Hanbin
  • [05/2020] A paper on differential privacy (DP) for video analysis is accepted to PETS'20 (Acceptance Rate: 23%). Congrats, Han and Shangyu
  • [04/2020] Yuan will give a tutorial on data privacy in DGO'20 (Digtal Government Research)
  • [04/2020] Yuan will teach CS528 Data Privacy and Security in Fall 2020
  • [03/2020] A paper on real-time privacy preserving energy trading system (MPC) is accepted to ICDCS'20 (Acceptance Rate: 18%). Congrats, Shangyu and Han

Selected Funded Projects

Research Areas and Selected Publications

  • Differential Privacy (including LDP)
    • DP Theory: R2DP [CCS'20]
    • DP for Videos: VideoDP [PETS'20], VERRO (RR based Indistinguishable Objects) [EDBT'20]
    • DP for Trajectories: VTDP [TDSC'19], Correlated Trajectories [TDSC'20]
    • DP for Query Logs (Text): Optimal Sampling [EDBT'12], Collaborative Sampling [TDSC'15]
    • DP for DM/ML: DP-NBC [WI'13]
  • AI Security and Privacy
    • ML Security Attacks: U3D on Video DNN [Oakland'22], LogBug [CIKM'20]
    • ML Privacy Attacks: Attacking Instance Encoding for NLP [EMNLP'21]
    • ML Security Defenses: TBD
    • ML for Privacy: Privacy Attribute Identification [ICPR'20]
    • Privacy Defenses (besides DP and Crypto): Private Smart Meter Streaming [TIFS'17]
  • Secure Multiparty Computation (Applied Cryptography)
  • ML and Optimization