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Address: 371 Fairfield Way
Unit 4155, Storrs, CT 06269

Office: ITE-265
Email: yuan.hong AT uconn.edu

Short Bio

Dr. Yuan Hong is a Collins Aerospace Associate Professor in Computer Science at University of Connecticut (UConn) and affiliated with the Connecticut Advanced Computing Center (CACC). Prior to joining UConn in 2022, he was an Assistant Professor in Computer Science and Cybersecurity Program Director at Illinois Institute of Technology. He received his Ph.D degree from Rutgers University, M.Sc degree from Concordia University, Montreal, Canada, and B.Sc degree from Beijing Institute of Technology, respectively. He is a recipient of the NSF CAREER Award (2021), Cisco Research Award (2022, 2023), and the finalist of the Meta Research Award (2021). He also received a National Physics Olympiad Prize in China. He is broadly interested in fundamental research in Security and Privacy (e.g., Differential Privacy, Secure Computation, Applied Cryptography, Adversarial Attacks, Provable Defenses) while intersecting with Cyber-Physical Systems, Machine Learning, Computer Vision, NLP, and Theory. His research works are published in Top Conferences in Security (e.g., S&P, and CCS), and Data Science (e.g., SIGMOD, VLDB, CVPR, ECCV, EMNLP, KDD, and AAAI). He is a Senior Member of the ACM and IEEE.

We are always looking for postdocs, Ph.D. students, visiting scholars/students, and undergraduate researchers. Please email your application materials to Dr. Yuan Hong if you are interested in our research.

UConn@CSRankings: Security & Crypto (30th), Overall (65th)


News

  • [02/2024] Yuan is appointed as the Collins Aerospace Professor with the term of 2024-2027 (very grateful for the generous support!)
  • [02/2024] Our work on the faithfulness of vision transformer explanations is accepted to CVPR'24. Congrats!
  • [02/2024] Our work on safeguarding user privacy in tool-using LLM agents is accepted to TDSC. Congrats, Xinyu!
  • [02/2024] Our work on strong LDP for federated learning is accepted to ACM CODASPY'24. Congrats, Varun (UG student)!
  • [12/2023] Our work on federated learning privacy against attribute inference attacks is accepted to AAAI'24. Congrats!
  • [11/2023] Our work on local differential privacy for data stream with bounded memory is accepted to SIGMOD'24. Congrats, Xiaochen!
  • [11/2023] Yuan will serve as the Associate Editor for the IEEE Transactions on Dependable and Secure Computing (TDSC).
  • [11/2023] Our Computer Science and Engineering (CSE) Department is now officially School of Computing.
  • [10/2023] Our work on strict user-level differential privacy for infinite data stream is accepted to S&P'24. Congrats, Shuya, Meisam and Han!
  • [10/2023] Yuan is elevated to the ACM Senior Member
  • [10/2023] Our new work on private information retrieval (PIR) with constant online cost is recently completed and released.
  • [10/2023] Yuan received the Cisco Research Award on certified robustness for emerging ML applications (very grateful to Cisco for the generous support!)
  • [09/2023] Our project on data poisoning attacks and infrastructure-enabled defenses for ITS (with Jeff Ban) is funded by the NSF CIS Program (very grateful to NSF for the generous support!)
  • [07/2023] Our work on certified defenses against adversarial attacks on language models is accepted to S&P'24. Congrats, Xinyu and Hanbin!
  • [07/2023] Our project on privately measuring the performance of cellular networks (with Bing Wang and Suining He) is funded by the NSF IMR Program (very grateful to NSF for the generous support!)
  • [07/2023] Our work on infrastructure-enabled GPS spoofing detection and correction is accepted to T-ITS. Congrats, Feilong!
  • [07/2023] Yuan will serve as the Associate Editor for the Elsevier Computer & Security.
  • [06/2023] Our work on attacking the interpretation model for electronic health records is accepted to ECML/PKDD'23. Congrats!

Research Areas and Recent/Selected Publications (source codes will be available on the publications page)

  • Differential Privacy
    • DP Mechanism Design (with New Randomization Theory):
      • [S&P'24] DPI: Strict DP for Infinite Data Streams
      • [CCS'20] R2DP: Optimal DP with Two-fold Randomization
    • Local Differential Privacy:
      • [SIGMOD'24] LDP Data Stream with Bounded Memory
      • [CODASPY'24] Staircase Randomized Response for Federated Learning
      • [VLDB'23] Distance-based LDP for Vertical Federated Tree Boosting
      • [CCS'22] Staircase Randomized Response
    • DP on Learning and Unstructured Data:
      • [KDD'22] Topic Mining with DP
      • [TDSC'21] Vehicle Trajectory Data Sanitization with DP
      • [PETS'20] DP Platform for Video Queries (VideoDP)
      • [EDBT'20] Queries over Videos with Indistinguishable Objects
      • [TDSC'20] Correlated Trajectories with Optimal DP
      • [EDBT'12, TDSC'15] Sampling Query Log/Textual Data with DP
      • [WI'13] DP Naive Bayes Classifier
  • Trustworthy Machine Learning: Security/Robustness, Privacy and Fairness
    • ML Security Attacks:
    • ML Certified Robustness and Empirical Defenses:
      • [S&P'24] Text-CRS on Language Models
      • [ECCV'22] Universal Certified Robustness
      • [preprint] Anisotropic Certified Robustness
      • [preprint] Defending against Gradient-based Attacks
    • ML Privacy:
      • [TDSC] PrivacyAsst: Safeguarding User Privacy in Tool-Using LLM Agents
      • [AAAI'24] Private Federated Learning Against Attribute Inference Attacks
      • [EMNLP'21] Attacking Instance Encoding for NLP
      • [ICPR'20] Privacy Attribute Identification
      • Please See Differential Privacy and Secure Multiparty Computation for More Privacy Defenses
    • Other Trustworthiness:
      • [CVPR'24] Faithfulness of Vision Transformer Explanations
  • Secure Multiparty Computation (MPC) and Cryptosystems
    • Private Information Retrieval (PIR)
      • [ePrint] Pai: PIR with Constant Online Time
    • CryptoDNN
    • Property-preserving Encryption
      • [ICDE'22, TKDE'21] Inference-proof Data Outsourcing with Prefix-preserving Encryption
      • [CCS'18, TOPS'21] Multi-view Network Trace Encryption/Anonymization
    • Cloud Privacy and Integrity
      • [TIFS'19] Live Forensics with Integrity in the Cloud
    • MPC Acceleration
      • [ICCD'19] Scheduling for Ring ORAM
  • Cyber-Physical Systems Security and Privacy
    • IoT Privacy
      • [TDSC'23] ASR Speech Privacy
      • [TIFS'17] Private Smart Meter Streaming against Inference Attacks
    • ITS and V2X
      • [T-ITS'23] GPS Spoofing Detection and Correction
      • [T-ITS'21] Dynamic Pricing for Electric Vehicles
    • MPC for Multi-agent Systems in the Smart Grid
      • [ICDCS'21] Private Double Auction for Energy (TEE-Blockchain)
      • [ICDCS'20] Distributed Energy Trading
      • [AAMAS'20] Private Double Auction for Energy (MPC)
      • [AAMAS'19, TIFS'20] Distributed Load Balancing (Privacy and Integrity)
      • [ICASSP'18] Private Energy Exchanging
  • Optimization

Teaching

  • Cybersecurity Lab: Fall 23, Spring 24
  • Computer Security: Spring 23
  • CSE Design Project: 2022-2023
  • Cryptography: Spring 21, Spring 20
  • Data Privacy and Security: Fall 21, Fall 20, Spring 19, Spring 18
  • Database Organization: Spring 22, Fall 19, Fall 18, Fall 17
  • Doctoral Seminar: Spring 18
  • Earlier Teaching: Cybercrime, Forensics, Computer Network