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)
• CESS: Computer Engineering and Software Systems (FS23)
• ComSys: Communication Systems (FS23)

• CNSP: Computer Network Security Principles (HS23)

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.

2023

• [arXiv ] Chao Feng, Alberto Huertas Celdran, Pedro Miguel Sanchez Sanchez, Jan Kreischer, Jan von der Assen, Gerome Bovet, Gregorio Martinez Perez, and Burkhard Stiller. "CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation." arXiv preprint arXiv:2308.05978 (2023).
• [arXiv ] Alberto Huertas Celdran, Chao Feng, Pedro Miguel Sanchez Sanchez, Lynn Zumtaugwald, Gerome Bovet, and Burkhard Stiller. "Assessing the Sustainability and Trustworthiness of Federated Learning Models." arXiv preprint arXiv:2310.20435 (2023).

• [arXiv ] Chao Feng, Alberto Huertas Celdran, Janosch Baltensperger, Enrique Tomas Matınez Bertran, Gerome Bovet, Burkhard Stiller. "Sentinel: An Aggregation Function to Secure Decentralized Federated Learning." arXiv preprint arXiv:2310.08097 (2023).

• [arXiv ] Chao Feng, Alberto Huertas Celdran, Michael Vuong, Gerome Bovet, Burkhard Stiller. "Voyager: MTD-Based Aggregation Protocol for Mitigating Poisoning Attacks on DFL." arXiv preprint arXiv:2310.08739 (2023).

• [arXiv ]  Figueredo Franco, Muriel, Fabian Künzler, Jan von der Assen, Chao Feng, and Burkhard Stiller. "RCVaR: an Economic Approach to Estimate Cyberattacks Costs using Data from Industry Reports." arXiv e-prints (2023): arXiv-2307.

• [arXiv ] Beltrán, Enrique Tomás Martínez, Ángel Luis Perales Gómez, Chao Feng, Pedro Miguel Sánchez Sánchez, Sergio López Bernal, Gérôme Bovet, Manuel Gil Pérez, Gregorio Martínez Pérez, and Alberto Huertas Celdrán. "Fedstellar: A Platform for Decentralized Federated Learning." arXiv preprint arXiv:2306.09750 (2023).

• [Full Paper]  Celdrán, Alberto Huertas, Pedro Miguel Sánchez Sánchez, Chao Feng, Gérôme Bovet, Gregorio Martínez Pérez, and Burkhard Stiller. "A Summary of Privacy-preserving and Syscall-based Intrusion Detection System for IoT Sensors Affected by Data Falsification Attacks." In Actas de las VIII Jornadas Nacionales de Investigación en Ciberseguridad: Vigo, 21 a 23 de junio de 2023, pp. 547-548. Universidade de Vigo, 2023.

• [Full Paper] Chao Feng, Jan von der Assen, Alberto Huertas Celdrán, Steven Näf, Gérôme Bovet, Burkhard Stiller:  FeDef: A Federated Defense Framework Using Cooperative Moving Target Defense; 2023 8th International Conference on Smart and Sustainable Technologies (SpliTech), Bol/Split, Croatia, June 2023, pp. 1-6.
• [Full Paper ] Katharina Olga Emilia Müller, Louis Bienz, Bruno Bastos Rodrigues, Chao Feng, Burkhard Stiller: HomeScout: Anti-Stalking Mobile App for Bluetooth Low Energy Devices; The 48th IEEE Conference on Local Computer Networks (LCN), Daytona Beach, Florida, U.S.A., October 2023, pp 1–8.  
• [Demo] Eryk Schiller, Chao Feng, Rafael Hengen Ribeiro, Francesco Marino, Martin Buck, Burkhard Stiller: TactSR: Utilizing SRv6 to Optimize the Routing Behavior for Tactical Networks; 2023 24th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Boston, USA, June 2023, pp. 1-3. 

2022

• [Full Paper] K. O. E. Müller, J. von der Assen, C. Feng, and B. Stiller, "An Overview and Ontology of Privacy to Preserve Privacy in Ultra-Wideband Networks," in IEEE International Conference on Privacy Computing, Haikou, China, December 2022, pp. 1-9. (To appear)

• [Full Paper] A. H. Celdrán, P. M. S. Sánchez, C. Feng, G. Bovet, G. M. Pérez and B. Stiller, "Privacy-preserving and Syscall-based Intrusion Detection System for IoT Spectrum Sensors Affected by Data Falsification Attacks," in IEEE Internet of Things Journal, 2022, doi: 10.1109/JIOT.2022.3213889. Link

• [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