Chao Feng

Chao Feng is pursuing a Ph.D. in the Department of Informatics at the University of Zurich. He obtained his MSc. in Informatics from the University of Zurich and a BSc. in Management Information System from Renmin University of China. Chao is currently working as a Ph.D. student and Junior Researcher in the Communication Systems Group, supervised by Prof. Dr. Burkhard Stiller. His research primarily focuses on enhancing the cybersecurity of Internet-of-Things (IoT) and improving the robustness of Decentralized Distributed Machine Learning systems,  especially for Decentralized Federated Learning (DFL).

• PMMK: Protocols for Multi-media Communications (HS22)
• IntEco: Internet Economics Seminar (HS22, HS23, HS24, HS25)
• CESS: Computer Engineering and Software Systems (FS23, FS24, FS25, FS26)
• ComSys: Communication Systems (FS23, FS24, FS25, FS26)

• CNSP: Computer Network Security Principles (HS23)

• CNDS: Computer Networks and Distributed Systemss (HS25)

Cybersecurity
Internet of Things (IoT)
Data Mining and Artificial Intelligence

Please check here to see list of open thesis. If you are interested to work on a project in the list mentioned above or any other project related to my research area feel free to contact me.

The list of my publications are available at the repositories maintained by Scholar, ORCID, and DBLP.

• [BA] Filip Trendafilov: Implementation of Membership Inference Attack Affecting Federated Learning-based Anomaly Detection System; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, May 2023, URL: link  
• [BA] Timothy-Till Näscher: Poisoning Attack Behavior Detection in Federated Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, May 2023, URL: link
• [BA] Michael Vuong: Design and Implementation of a Byzantine Robust Aggregation Mechanism for Decentralized Federated Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2023, URL: link
• [MA] Janosch Baltensperger: A Secure Aggregation Protocol for Decentralized Federated Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2023, URL: link
• [BA] Florian Andreas Herzog: Fully Fledged SDN in a LoRa Mesh; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, September 2023, URL: link
• [BA] Gregory Frommelt: Linux on Tensilica Xtensa; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, September 2023, URL: link
• [MA] Lynn Zumtaugwald: Designing and Implementing an Advanced Algorithm to Measure the Trustworthiness Level of Federated Learning Models; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2023, URL: link
• [MA] Róbert Oles: Detection and Classification of Malware using File System Dimensions for MTD on IoT; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, May 2023, URL: link
• [MA] Jan Kreischer: Federated Reinforcement Learning for Private and Collaborative Selection of Moving Target Defense Mechanisms for IoT Device Security; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, June 2023, URL: link
• [MA] Chenfei Ma: Design and Prototypical Implementation of the Node Selection Strategy in Federated Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, October 2023, URL: link
• [MAP] Han, Jing and Cheng, Xi and Zeng, Zien and Ren, Heqing: Creation of New Datasets for Decentralized Federated Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, Jan. 2024, URL: link
• [MA] Ye Zi: Mitigating Poisoning Attacks in Decentralized Federated Learning through Moving Target Defense; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, Mar. 2024, URL: link  
• [IS] Yuanzhe Gao: Design and Implementation of a Privacy Auditing Component for the Decentralized Federated Learning Framework; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, Jun. 2024, URL: link  

• [MA] Xiao Chen: Design and Implementation of an Information Metrics-based Anomaly Model Detector in Decentralized
  Federated Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, Jul. 2024, URL: link 

• [MA] Hongjie Guan: FedEP: Tailoring Attention to Heterogeneous Data Distribution with Entropy Pooling; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, Jul. 2024, URL: link 

• [MA] Xi Cheng: Design and Implementation of Environmental Sustainability Module for Decentralized Federated Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2024, URL: link

• [MA] Wenzhe Li: Design and Implementation of a Black-box Robustness Analysis Module for an DFL Platform; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2024, URL: link
• [MA] Zien Zeng: Improving the Model Robustness of DFL in Non-IID Environment; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2024, URL: link
• [MAP] Runxi Cui, Yunlong Li: Novel Poisoning Attacks on Decentralized Federated Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2024, URL: link
• [IS] Lucas Krauter: Data Exploration and Feature Engineering for an IoT Device Behavior Fingerprinting Dataset; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2024, URL: link
• [MA] Yuanzhe Gao: Novel Topology Inference Attacks on DFL; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, October 2024, URL: link
• [MA] Nicolas Kohler: A Solution for Decentralized Federated Multi-Task Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, October 2024, URL: link
• [MAP] Timothy-Till Näscher, Witold Rozek: Feature Integration for an Open-source Decentralized Federated Learning Platform; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, January 2025, URL: link.
• [MAP] Nazek Olabi, Michael Vuong: Dimensionality Reduction for Distributed Machine Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, April 2025, URL:link
• [BA] Nicolas Huber: Deploying a Decentralized Federated Learning Platform in Resource-Constrained Devices; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, April 2025, URL: link
• [MA] Heqing Ren: Design and Implementation of an MTD-based Mitigation Approach for Membership Inference Attacks; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, April 2025, URL: link
• [MA] Zihan Liu: Design and Implementation of an AI-based Agent to Inform Best Practices on Test Case Execution Routines; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, July 2025, URL: link
• [MA] Zhi Wang: Attack Strategies and Robustness Certification in Decentralized FMTL Systems; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2025, URL:  link.
• [BA] Arbër Markaj: A Framework to Detect Data Poisoning Attacks in Decentralized Federated Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2025, URL: link.
• [MA] Timothy-Till Näscher: Design and Implementation of a Lightweight Decentralized Federated Learning Platform; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, August 2025, URL: link.
• [MAP] Sandrin Hunkeler, Linn Spitz: Peer-Based Mixing for Decentralized Federated Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, September 2025, URL: link.
• [MA] Xi Chen: Dynamic Task Clustering and Aggregation for Decentralized Federated Multitask Learning; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, January 2026, link.
• [MAP] Niklas Schmidt, Elias Müller: Design and Prototypical Implementation of Decentralised Federated Object Detection; Universität Zürich, Communication Systems Group, Department of Informatics, Zürich, Switzerland, February 2026, link.