Chong Yu, Ph.D.

Assistant Professor
Department of Computer Science
University of Cincinnati
Cincinnati, Ohio 45221

Office: Rhodes Hall 887
Phone: 513-556-7904
Research Lab: Rhodes Hall 800A
Email: yuc5 at ucmail dot uc dot edu
Curriculum Vitae

Bio

She received her Ph.D. degree in Electrical and Computer Engineering from the University of Nebraska-Lincoln, Lincoln, USA in 2023, and another Ph.D. in degree Computer Science from Northeastern University, Shenyang, China in 2022. Her research interests include distributed computing, machine learning, cybersecurity and privacy, with a broad range of applications including data analytics, edge-based artificial intelligence, and Internet of Things.

Hiring: I am seeking self-motivated students who have interests in the following areas, including but not limited to AI, federated learning, and cybersecurity. Here is the details.

News

• 10/2024: Dr. Yu delivered a invited research talk “Hybrid Federated Learning for E-health with Horizontal and Vertical Data Partitioning” in SISSC 2024!
• 10/2024: Our paper “Secure and Efficient Federated Learning Against Model Poisoning Attacks in Horizontal and Vertical Data Partitioning” is accepted by IEEE TNNLS! Congrats!
• 10/2024: Our paper “JSMBox - A Runtime Monitoring Framework for Analyzing and Classifying Malicious JavaScript” is selected as “Best Paper Award” in SEDE 2024! Congrats!
• 08/2024: Dr. Yu serves on the organizaing committee for ISICN 2025 (San Juan, Pueto Rico). Please consider submitting papers to ISICN 2025.
• 07/2024: Our paper “JSMBox - A Runtime Monitoring Framework for Analyzing and Classifying Malicious JavaScript” is accepted by SEDE 2024! Congrats!
• 07/2024: Dr. Yu delivered a invited research talk “Artifical Intelligence & Machine Learning” in IEEE NAECON 2024!
• 07/2024: Our paper “Code Comprehension: Review and Large Language Models Exploration” is selected as “Best Paper Award” in IEEE SEAI 2024! Congrats!
• 04/2024: Our paper “Code Comprehension: Review and Large Language Models Exploration” is accepted by IEEE SEAI 2024! Congrats!
• 03/2024: Our paper “Communication-Efficient Hybrid Federated Learning for E-health with Horizontal and Vertical Data Partitioning” is accepted by IEEE TNNLS! Congrats!
• 02/2024: Dr. Yu attended 2024 CRA Career Mentoring Workshops in Washington, D.C..
• 01/2024: Our paper “Secure Interaction-based Feature Selection for Vertical Federated Learning” is accepted by IEEE ICC 2024! Congrats!
• 01/2024: Our paper “Explore Patterns to Detect Sybil Attack during Federated Learning in Mobile Digital Twin Network” is accepted by IEEE ICC 2024! Congrats!
• 01/2024: Our paper “Detecting Poisoning Attacks with DynaDetect” is accepted by ISICN 2024! Congrats!
• 01/2024: Our paper “Privacy-Preserving Anomaly Detection of Encrypted Smart Contract for Blockchain-Based Data Trading” is accepted by IEEE TDSC! Congrats!
• 11/2023: Our paper “LSPSS: Constructing Lightweight and Secure Scheme for Private Data Storage and Sharing in Aerial Computing” is accepted by IEEE TSC! Congrats!

Selected Recent Publications

Journal Publications

• C. Yu, Z. Meng, W. Zhang, L. Lei, J. Ni, K. Zhang, and H. Zhao, “Secure and Efficient Federated Learning Against Model Poisoning Attacks in Horizontal and Vertical Data Partitioning,” IEEE Transactions on Neural Networks and Learning Systems, 2024.
• C. Yu, S. Shen, S. Wang, K. Zhang, and H. Zhao, “Communication-Efficient Hybrid Federated Learning for E-health with Horizontal and Vertical Data Partitioning,” IEEE Transactions on Neural Networks and Learning Systems, 2024.
• D. Chen, Z. Liao, R. Chen, H. Wang, C. Yu, K. Zhang, N. Zhang, and X. Shen, “Privacy-Preserving Anomaly Detection of Encrypted Smart Contract for Blockchain-Based Data Trading,” IEEE Transactions on Dependable and Secure Computing, 2024.
• H. Wang, K. Fan, C. Yu, K. Zhang, F. Li, H. Li, Y. Yang, and H. Zhu, “LSPSS: Constructing Lightweight and Secure Scheme for Private Data Storage and Sharing in Aerial Computing,” IEEE Transactions on Services Computing, 2023.
• C. Yu, S. Shen, H. Yang, K. Zhang, and H. Zhao, “Leveraging Energy, Latency and Robustness for Routing Path Selection in Internet of Battlefield Things,”IEEE Internet of Things Journal, vol.9, no.14, pp.12601-12613, 2022.
• S. Shen, C. Yu, K. Zhang, J. Ni, and S. Ci, “Adaptive Artificial Intelligence for Resource-Constrained Connected Vehicles in Cybertwin-Driven 6G Network,” IEEE Internet of Things Journal, vol.8, no.22, pp.16269-16278, 2021.
• S. Shen, C. Yu, K. Zhang, J. Ni, and S. Ci, “Adaptive and Dynamic Security in AI-Empowered 6G: From an Energy Efficiency Perspective,” IEEE Communications Standards Magazine, vol.5, no.3, pp.80-88, 2021.
• S. Si, B. Wang, X. Liu, C. Yu, C. Ding, and H. Zhao, “Brain Network Modeling based on Mutual Information and Graph Theory for Predicting the Connection Mechanism in the Progression of Alzheimer's Disease,,” Entropy, vol.21, no.3, pp.300-318, 2019. (IF: 2.1)
• C. Yu, S. Si, H. Guo, and H. Zhao, “Modeling and Performance of the IEEE 802.11p Broadcasting for Intra-Platoon Communication,,” Sensors, vol.18, no.9, pp.2971-2986, 2018. (IF: 3.4)
• S. Si, J. Wang, C. Yu, and H. Zhao, “Energy-Efficient and Fault-Tolerant Evolution Models based on Link Prediction for Large-Scale Wireless Sensor Networks,,” IEEE Access, vol.6, pp.73341-73356, 2018. (IF: 3.9)

Conference Papers

• P. Phung, A. Varghese, B. Wang, Y. Zhao, and C. Yu, “JSMBox - A Runtime Monitoring Framework for Analyzing and Classifying Malicious JavaScript,” in Proc. of SEDE 2024, San Diego, USA, Oct. 2024, pp. 100-122.
• J. Cui, Y. Zhao, C. Yu, J. Huang, Y. Wu, and Y. Zhao, “Code Comprehension: Review and Large Language Models Exploration,” in Proc. of IEEE SEAI 2024, Xiamen, China, June 2024, pp. 183-187.
• Z. Meng, W. Zhang, S. Shen, C. Yu, and K. Zhang, “Secure Interaction-based Feature Selection for Vertical Federated Learning,” in Proc. of IEEE ICC’24, Denver, USA, June 2024, pp. 4608-4613.
• W. Zhang, C. Yu, Z. Meng, S. Shen, and K. Zhang, “Explore Patterns to Detect Sybil Attack during Federated Learning in Mobile Digital Twin Network,” in Proc. of IEEE ICC’24, Denver, USA, June 2024, pp. 3969-3974.
• S. Perry, Y. Jiang, F. Zhong, and C. Yu, “Detecting Poisoning Attacks with DynaDetect,” in Proc. of ISICN, San Juan, Puerto Rico, USA, March 2024, pp. 241-255.
• Z. Meng, C. Yu, and Q. Yi, “Privacy-preserving Task Allocation and Decentralized Dispute Protocol in Mobile Crowdsourcing,” in Proc. of IEEE ICC'23, Rome, Italy, June 2023, pp. 1579-1584.
• C. Yu, S. Shen, S. Wang, K. Zhang, and H. Zhao, “Efficient Multi-Layer Stochastic Gradient Descent Algorithm for Federated Learning in E-health,” in Proc. of IEEE ICC'22, Seoul, South Korea, May 2022, pp. 1263-1268.
• S. Shen, C. Yu, K. Zhang, and S. Ci, “Collaborative Edge Caching with Personalized Modeling of Content Popularity over Indoor Mobile Social Networks,” in Proc. of IEEE ICC'22, Seoul, South Korea, May 2022, pp. 4114-4119.
• C. Yu, S. Shen, K. Zhang, H. Zhao, and Y. Shi, “Energy-Aware Device Scheduling for Joint Federated Learning in Edge-assisted Internet of Agriculture Things,” in Proc. of IEEE WCNC'22, Austin, USA, Apr. 2022, pp. 1140-1145.
• W. Yao, K. Zhang, C. Yu, and H. Zhao, “Exploiting Ensemble Learning for Edge-assisted Anomaly Detection Scheme in e-healthcare System,” in Proc. of IEEE Globecom'21, Madrid, Spain, Dec. 2021, pp. 1-7.
• S. Shen, C. Yu, K. Zhang, X. Chen, H. Chen, and S. Ci, “Communication-Efficient Federated Learning for Connected Vehicles with Constrained Resources,” in Proc. of IEEE IWCMC, Harbin, China, Jun. 2021, pp. 1636-1641.
• S. Shen, C. Yu, K. Zhang, and S. Ci, “Exploiting Feature Interactions for Malicious Website Detection with Overhead-accuracy Tradeoff,” in Proc. of IEEE ICC'21, Montreal, Canada, Jun. 2021, pp. 1-7.

Teaching

• CS 7005: Advanced Special Topics in Computer Science: Trustworthy Machine Learning (Spring 2025), University of Cincinnati
• CS 2028C: Data Structures (Fall 2024), University of Cincinnati
• CS 2028C: Data Structures (Fall 2023), University of Cincinnati