Zhiyu Zhang
PhD Candidate of Cyberspace security
Institute of Information Engineering, Chinese Academy of Sciences
Biography
Zhiyu Zhang is a PhD candidate in Institute of Information Engineering, Chinese Academy of Sciences supervised by Prof. Kai Chen.
Zhiyu Zhang received his bachelor degree in School of Electronic Information and Communications, Huazhong University of Science and Technology. He used to work as the Cyber Security Group member of Dian Group (Official ID: D637), advised by Guohui Zhong, Chengwei Zhang, Yayu Gao and Xiaojun Hei.
His Research interests lie within Software and System Security, particularly in Program Analysis and Fuzzing techniques. Besides, he is also widely interested in Blockchain and AI Security.
(Notice: The pages below have not been updated, please refer to my CV)
- Fuzzing
- Deep Learning
- Algorithm & CTF
Ph.D in Cyberspace security, 2021
Institute of Information Engineering, Chinese Academy of Sciences
B.Eng in Electronic Information Engineering, 2017
Huazhong University of Science and Technology
Senior High School, 2014
NO.1 Middle School attached to CCNU
Experience
This is a Course Design aiming at providing convenient service of Online NS-3 environment and tutorials to the beginners and researchers, which covers the techniques of Concurrency Process, Nodejs-Vue and NS-3 Docker Cloud.
My responsibilities include:
- Propose and implement an online NS-3 server with Vue, Nodejs and NS-3 engine, as the installation and con guration of NS-3 are complicated.
- Provide tutorial pages and relevant experiment guidelines on the Web UI.
- Adopt polling queue to improve the effciency of NS-3 compiling, effciency improved around 4x. (Submitted to SIMUtools 2020)
This is a national project aiming at the research of Intrusion Detection and Prevention Systems, which covers the techniques of Reverse Engineering, Netmap, ATT&CK, Network Traffic Detection and Deep Learning.
My responsibilities include:
- Propose a Fast Recoverable System for Cyber Range in order to conduct destructive experiments effciently. (Oral presentation on IEEE ICTC 2020)
- Analyze the execution principles of malware based on reverse engineering | e.g. WannaCry would scan 445 port of the public IP and send payload by overflow of SMB I.
- Based on the analysis of malware principles, leveraged the spatial and timing features to detect malicious traffc with pattern matching and deep learning | e.g. We managed to detect almost 100% nmap scan. (Submitted to Cybersecurity 2020)
Inverse problem in structures is to rebuild the physical situation of a damaged structure throught the collected data. This Smart City project covers the techniques of Finite Element Analysis and Deep Learning and is supervised by Prof. Shaofan Li. In the summer research, we take cantilever as a research target.
My responsibilities include:
- Adopt FEA method to simulate the physical principles of cantilever.
- Use tensorflow to build deep neural network and make prediction of the initial status of the cantilever.
- Make temperature prediction of bridge based on DSP methods and machine learning. (Paper being prepared for Applied Science)
This is a Enterprise-level project aiming at providing secure agent service for Samba directory sharing, which covers the techniques of Windows Driver Development, Linux Kernel, advanced TCP/IP.
My responsibilities include:
- Develop windows network driver according to Microsoft WDK API.
- Parse samba 2 protocol to dump the files during the directory sharing.
- Improve performance by setting up LVS load balancing servers.
