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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 an Associate Professor in the Department of Computer Science & Engineering 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, Cisco Research Award, and the finalist of the Meta Research Award. 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 CS venues, such as S&P/Oakland, CCS, PETS, KDD, ECCV, EMNLP, VLDB, ICDE, EDBT, AAMAS, CIKM, ICDCS, TDSC, TIFS, TOPS and TKDE.

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 (33rd), Overall (66th)

News

  • [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/Oakland'24 (Acceptance Rate: TBD, PDF, Code). 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!
  • [06/2023] Our work on attacking the interpretation model for electronic health records is accepted to ECML/PKDD'23 (Acceptance Rate: 24%, Code). Congrats!
  • [04/2023] Congrats to Dr. Han Wang on successfully defending her Ph.D. dissertation on Differential Privacy. She will join the University of Kansas as a Tenure-Track Assistant Professor. Congrats!
  • [01/2023] Our work on IoT speech privacy with non-targeted universal adversarial perturbations is accepted to TDSC. Congrats!
  • [11/2022] Congrats to Dr. Bingyu Liu on successfully defending her Ph.D. dissertation on Boosting the Utility and Efficiency of Private Data Analysis. She will join Northeastern University as a Postdoctoral Researcher
  • [10/2022] Congrats to Hanbin on receiving the Synchrony Fellowship (very grateful to Synchrony and CACC for the generous support)
  • [10/2022] Congrats to Dr. Shangyu Xie on successfully defending his Ph.D. dissertation on Trustworthy Multi-Agent and Machine Learning Systems. He will join Amazon as an Applied Scientist
  • [10/2022] Yuan will teach CSE 4400/5400 Computer Security in Spring 2023
  • [10/2022] Congrats to Han, Hanbin and Bingyu on receiving the CCS'22 Student Travel Award (very grateful to CCS'22 for the generous support)
  • [09/2022] Our work on order-preserving desensitization for vertical federated tree boosting is accepted to VLDB'23 (Acceptance Rate: 24.8%, PDF, Code). Congrats!
  • [09/2022] Our work on cryptographic systems for video inference (Crypto3D) is accepted to the poster track of CCS'22. Congrats, Bingyu!
  • [08/2022] Yuan will be advising the CSE Senior Design in the Academic Year 2022-2023
  • [07/2022] Our paper on the new staircase randomized response mechanism (ensuring LDP for Location-Based Services) is accepted to CCS'22 (Acceptance Rate: 22.4%, Direct Accept: 7.81%, PDF, Code). Congrats, Han and Hanbin!
  • [07/2022] Our paper on universal certified robustness against any p-norm perturbations is accepted to ECCV'22 (Acceptance Rate: 28%, PDF, Code). Congrats, Hanbin!
  • [06/2022] After working at Illinois Tech for five wonderful years (and commuting between Chicago and New England), Yuan and DataSec Lab will move to the CSE Department at the University of Connecticut. Thanks everyone at Illinois Tech!
  • [05/2022] Our Code [in Rust and Python] for the Universal 3-Dimensional (U3D) attacks (S&P/Oakland'22) is released!
  • [05/2022] A model-agnostic approach to differentially private topic mining is accepted to KDD'22 (Acceptance Rate: 14.99%, PDF, Code). Congrats, Han, Jayashree and Shuya
  • [05/2022] The preliminary result of differentially private instance encoding is accepted to NAACL-SRW'22. Congrats, Shangyu
  • [04/2022] Kai and Yuan received the Cisco Research Award on Explainable AI with Fairness and Privacy (very grateful to Cisco for the generous support)
  • [03/2022] A paper on video data poisoning attack is accepted to TDSC. Congrats, Shangyu
  • [03/2022] Meisam will join the Department of Computer Science at Iowa State University as a Tenure-Track Assistant Professor. Congrats!

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

  • Differential Privacy
    • Local Differential Privacy:
      • [VLDB'23] Distance-based LDP for Vertifical Federated Tree Boosting
      • [CCS'22] Staircase Randomized Response
    • Optimal DP Mechanism Design (DP Theory):
      • [CCS'20] R2DP with Two-fold Randomization
    • 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

  • Secure Multiparty Computation (MPC) and Cryptosystems
    • 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

  • 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:
      • [EMNLP'21] Attacking Instance Encoding for NLP
      • [ICPR'20] Privacy Attribute Identification
      • ML Privacy Defenses: see Differential Privacy and Secure Multiparty Computation

  • 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 Investigation, E-Discovery Forensics, Computer Network