上海交通大学，网络空间安全学院，博士（吴文俊人工智能荣誉博士班）

流量分析：加密流量分析，匿名网络分析，网络入侵检测等。

Web安全：网页指纹识别，Webshell检测，验证码破解等。

主要研究方向包括流量分析和Web安全，通过结合人工智能技术赋能网络安全任务，解决网络安全领域中的一系列前沿挑战和落地需求。近年来在网络安全与人工智能领域顶级会议（IEEE S&P、USENIX Security、KDD、AAAI、IJCAI等）和主要期刊（IEEE/ACM TON、IEEE TFS、IEEE TII等）发表高水平论文20余篇。在相关领域担任KDD、WWW、ICLR、NeurIPS、IEEE TIFS、IEEE TDSC、IEEE TNSE、网络与空间安全学报、通信学报等多个国内外顶级会议及期刊审稿人。

流量分析的相关研究中，面向流量行为复杂多变、流量数据标注困难、流量数据隐私性强、边缘设备计算性能弱等诸多挑战，设计了强隐蔽性流量细粒度识别方法、流量数据自信息挖掘方法、跨域复杂流量协同训练方法、流量分析模型轻量化部署方法等解决方案。

Web安全的相关研究中，面向Web安全研究中的网页指纹识别、验证码破解、webshell检测三个关键场景开展研究。面向网页指纹隐藏机制，复杂验证码识别困难、webshell多样化混淆机制等诸多挑战，设计了网页指纹鲁棒识别方案、高效验证码求解器、代码语义感知的webshell检测等解决方案。

招收硕士生、本科实习生

目前正招收2025秋季入学研究生、本科实习生，致力于维护一个兴趣驱动、氛围融洽的网络安全课题研究小组，研究方向包括但不限于流量分析和Web安全，以利于学生长期发展为目标，可保证持续有效的指导沟通，并结合学生特点和意愿调整指导模式，可推荐优秀学生至海内外著名高校交流深造。

希望新加入的同学：

    - 有兴趣从事网络安全与人工智能领域的科学研究； 

    - 积极主动、热情开朗、有自驱力、有毅力； 

    - 具有扎实的编程能力，良好的英文阅读、写作与沟通能力； 

    - 有长远理想、目标，有志于推动团队、社区、领域发展。

欢迎具有网络安全、计算机、通信工程、人工智能等相关专业背景的同学与我通过邮件联系，请将你的简历、成绩单、研究背景或者其他能够展示个人能力的材料发送至我的邮箱。

2023.12  博士研究生国家奖学金

2023.12  《信息网络安全》期刊优秀审稿人

2022.12  上海交通大学张良起奖学金

2021.03  上海交通大学优秀毕业生

2024代表性论文

[1] R. Zhao, M. Zhan, X. Deng, F. Li, Y. Wang, Y. Wang, G. Gui, Z. Xue, A Novel Self-Supervised Framework Based on Masked Autoencoder for Traffic Classification, IEEE/ACM Transactions on Networking (IEEE/ACM TON), vol. 32, no. 3, pp. 2012-2025, 2024. (网络领域顶刊，CCF-A)

[2] H. He, X. Lin, Z. Weng, R. Zhao, S. Gan, L. Chen, Y. Ji, J. Wang, Z. Xue, Code is not Natural Language: Unlock the Power of Semantics-Oriented Graph Representation for Binary Code Similarity Detection, in 33rd USENIX Security Symposium, Philadelphia, United States, Aug. 14-16, 2024, pp.1-18. (四大安全顶会，CCF-A)

[3] W. Du, J. Li, Y. Wang, L. Chen, R. Zhao, J. Zhu, Z. Han, Y. Wang, Z. Xue, Vulnerability-oriented Testing for RESTful APIs, in 33rd USENIX Security Symposium, Philadelphia, United States, Aug. 14-16, 2024, pp.1-18. (四大安全顶会，CCF-A)

[4] T. Yuan, Z. He, L. Dong, Y. Wang, R. Zhao, T. Xia, L. Xu, B. Zhou, F. Li, Z. Zhang, R. Wang, G. Liu, R-Judge: Benchmarking Safety Risk Awareness for LLM Agents, in Conference on Empirical Methods in Natural Language Processing (EMNLP), Miami, United States, Nov. 12-16, 2024, pp.1-12. (CCF-B)

[5] Y. Wang, Z. Zhou, W. Bai, R. Zhao, X. Deng, CaptchaSAM: Segment Anything in Text-based Captchas, in IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Sanya, China, Dec. 17-21, 2024, pp.1-7. (CCF-C)

2023代表性论文

[1] R. Zhao, X. Deng, Y. Wang, Z. Yan, Z. Han, L. Chen, Z. Xue, Y. Wang, GeeSolver: A Generic, Efficient, and Effortless Solver with Self-Supervised Learning for Breaking Text Captchas, in IEEE Symposium on Security and Privacy (IEEE S&P), San Francisco, United States, May 22-24, 2023, pp. 1-18. (四大安全顶会，CCF-A)

[2] R. Zhao, M. Zhan, X. Deng, Y. Wang, Y. Wang, G. Gui, Z. Xue, Yet Another Traffic Classifier: A Masked Autoencoder Based Traffic Transformer with Multi-Level Flow Representation, in AAAI Conference on Artificial Intelligence (AAAI), Washington, United States, Feb. 7-14, 2023, pp. 1-8. (人工智能顶会，CCF-A)

[3] R. Zhao, Y. Huang, X. Deng, Y. Shi, J. Li, Z. Huang, Y. Wang, Z. Xue, A Novel Traffic Classifier with Attention Mechanism for Industrial Internet of Things, IEEE Transactions on Industrial Informatics (IEEE TII), vol. 19, no. 11, pp. 10799-10810, 2023. (Q1-Top, IF: 11.65)

[4] R. Zhao, Y. Wang, Z. Xue, T. Ohtsuki, B. Adebisi, G. Gui, Semisupervised Federated-Learning-Based Intrusion Detection Method for Internet of Things, vol. 10, no. 10, pp. 8645-8657, 2023. (Q1-Top, IF: 10.24)

[5] J. Zhu, Y. Yao, X. Deng, Y. Yong, Y. Wang, L. Chen, Z. Xue, R. Zhao, SAWD: Structural-Aware Webshell Detection System with Control Flow Graph, in International Conference on Software Engineering and Knowledge Engineering (SEKE), Pittsburgh, USA, Jul. 1-10, 2023, pp. 1-6. (CCF-C)

[6] Z. Yan, S. Li, R. Zhao, Y. Tian, Y. Zhao, DHBE: Data-free Holistic Backdoor Erasing in Deep Neural Networks via Restricted Adversarial Distillation, in ACM ASIA Conference on Computer and Communications Security (AsiaCCS), Melbourne, Australia, Jul. 10-14, 2023, pp. 1-15. (CCF-C)

2022代表性论文

[1] R. Zhao, X. Deng, Z. Yan, J. Ma, Z. Xue, Y. Wang, MT-FlowFormer: A Semi-Supervised Flow Transformer for Encrypted Traffic Classification, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Washington, United States, Aug. 14-18, 2022, pp. 1-9. (人工智能顶会，CCF-A)

[2] R. Zhao, X. Deng, Y. Wang, L. Chen, M. Liu, Z. Xue, Y. Wang, Flow Sequence-Based Anonymity Network Traffic Identification with Residual Graph Convolutional Networks, in IEEE/ACM International Symposium on Quality of Service (IWQoS), Virtual Conference, Jun. 10-12, 2022, pp. 1-10. (CCF-B)

[3] R. Zhao, G. Gui, Z. Xue, J. Yin, T. Ohtsuki, B. Adebisi, H. Gacanin, A Novel Intrusion Detection Method Based on Lightweight Neural Network for Internet of Things, IEEE Internet of Things Journal, vol. 9, no. 12, pp. 9960-9972, 2022. (Q1-Top, IF: 10.24)

[4] R. Zhao, T. Tang, G. Gui, Z. Xue, A Lightweight Semi-supervised Learning Method Based on Consistency Regularization for Intrusion Detection, in IEEE International Conference on Communications (ICC), Seoul, South Korea, May 16-20, 2022, pp. 1-6. (CCF-C)

[5] X. Deng, R. Zhao, Y. Wang, L. Chen, Y. Wang, Z. Xue, 3E-Solver: An Effortless, Easy-to-Update, and End-to-End Solver with Semi-supervised Learning for Breaking Text-Based Captchas, in 31st International Joint Conference on Artificial Intelligence (IJCAI), Vienna, Austria, Jul. 23-29, 2022, pp. 1-7. (人工智能顶会，CCF-A)

[6] F. Li, R. Zhao, S. Wang, L. Chen, A. Liew, W. Ding, Online Intrusion Detection for IoT Systems with Full Bayesian Possibilistic Clustering and Ensembled Fuzzy Classifiers, IEEE Transactions on Fuzzy Systems, vol. 30, no. 11, pp. 4605-4617, 2022. (Q1-Top, IF: 12.25)

Before 2022

[1] R. Zhao, J. Yin, Z. Xue, G. Gui, B. Adebisi, T. Ohtsuki, H. Gacanin, H. Sari, An Efficient Intrusion Detection Method Based on Dynamic Autoencoder, IEEE Wireless Communications Letters, vol. 10, no. 8, pp. 1707-1711, 2021. (Q2, IF: 5.28)

[2] R. Zhao, Y. Huang, X. Deng, Z. Xue, J. Li, Z. Huang, Y. Wang, Flow Transformer: A Novel Anonymity Network Traffic Classifier with Attention Mechanism, in 17th International Conference on Mobility, Sensing and Networking (MSN), Exeter, UK, Dec. 13-15, 2021, pp. 1-8. (CCF-C)

[3] R. Zhao et al., An Efficient and Lightweight Approach for Intrusion Detection Based on Knowledge Distillation, in IEEE International Conference on Communications (ICC), Montreal, Canada, Jun. 14-23, 2021, pp. 1-6. (CCF-C) 

[4] R. Zhao et al., A Novel Approach Based on Lightweight Deep Neural Network for Network Intrusion Detection, in IEEE Wireless Communications and Networking Conference (WCNC), Nanjing, China, Mar. 29 - Apr. 1, 2021, pp. 1-6. (CCF-C)

[5] X. Deng, R. Zhao, Z. Xue, M. Liu, L. Chen, Y. Wang, A Semi-supervised Deep Learning-Based Solver for Breaking Text-Based CAPTCHAs, in IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Shenyang, China, Oct. 20-22, 2021, pp. 1-6. (CCF-C)