Ruijie Zhao
Orcid: 0000-0001-6168-8687Affiliations:
- Shanghai Jiao Tong University, Shanghai, China
According to our database1,
Ruijie Zhao
authored at least 25 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
A Novel Self-Supervised Framework Based on Masked Autoencoder for Traffic Classification.
IEEE/ACM Trans. Netw., June, 2024
Code is not Natural Language: Unlock the Power of Semantics-Oriented Graph Representation for Binary Code Similarity Detection.
Proceedings of the 33rd USENIX Security Symposium, 2024
Proceedings of the 33rd USENIX Security Symposium, 2024
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
2023
A Novel Traffic Classifier With Attention Mechanism for Industrial Internet of Things.
IEEE Trans. Ind. Informatics, November, 2023
Semisupervised Federated-Learning-Based Intrusion Detection Method for Internet of Things.
IEEE Internet Things J., May, 2023
GeeSolver: A Generic, Efficient, and Effortless Solver with Self-Supervised Learning for Breaking Text Captchas.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023
Proceedings of the 35th International Conference on Software Engineering and Knowledge Engineering, 2023
DHBE: Data-free Holistic Backdoor Erasing in Deep Neural Networks via Restricted Adversarial Distillation.
Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, 2023
Yet Another Traffic Classifier: A Masked Autoencoder Based Traffic Transformer with Multi-Level Flow Representation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Online Intrusion Detection for Internet of Things Systems With Full Bayesian Possibilistic Clustering and Ensembled Fuzzy Classifiers.
IEEE Trans. Fuzzy Syst., 2022
SEAF: A Scalable, Efficient, and Application-independent Framework for container security detection.
J. Inf. Secur. Appl., 2022
A Novel Intrusion Detection Method Based on Lightweight Neural Network for Internet of Things.
IEEE Internet Things J., 2022
MT-FlowFormer: A Semi-Supervised Flow Transformer for Encrypted Traffic Classification.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Flow Sequence-Based Anonymity Network Traffic Identification with Residual Graph Convolutional Networks.
Proceedings of the 30th IEEE/ACM International Symposium on Quality of Service, 2022
3E-Solver: An Effortless, Easy-to-Update, and End-to-End Solver with Semi-Supervised Learning for Breaking Text-Based Captchas.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
A Semi-Supervised Federated Learning Scheme via Knowledge Distillation for Intrusion Detection.
Proceedings of the IEEE International Conference on Communications, 2022
A Lightweight Semi-Supervised Learning Method Based on Consistency Regularization for Intrusion Detection.
Proceedings of the IEEE International Conference on Communications, 2022
2021
IEEE Wirel. Commun. Lett., 2021
A Novel Approach based on Lightweight Deep Neural Network for Network Intrusion Detection.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2021
Proceedings of the 20th IEEE International Conference on Trust, 2021
Flow Transformer: A Novel Anonymity Network Traffic Classifier with Attention Mechanism.
Proceedings of the 17th International Conference on Mobility, Sensing and Networking, 2021
An Efficient and Lightweight Approach for Intrusion Detection based on Knowledge Distillation.
Proceedings of the ICC 2021, 2021
2020
Intelligent intrusion detection based on federated learning aided long short-term memory.
Phys. Commun., 2020
2018
Int. J. Commun. Syst., 2018