Recommended citation: Qiang Li, Yunan Zhang, Liya Su, et al. An Improved Method to Unveil Malware’s Hidden Behavior. International Conference on Information Security and Cryptology. Springer, Cham, 2017: 362-382.

Recommended citation: Qiang Li, Yunan Zhang, Liya Su, et al. An Improved Method to Unveil Malware Hidden Behavior. Inscrypt 2017: 362-382.

Hierarchical Clustering Based Network Traffic Data Reduction for Improving Suspicious Flow Detection Hierarchical Clustering Based Network Traffic Data Reduction for Improving Suspicious Flow Detection

Published in TrustCom/BigDataSE 2018, 2018

Download paper here

Recommended citation: Liya Su, Yepeng Yao, Ning Li, Junrong Liu, Zhigang Lu, Baoxu Liu. Hierarchical Clustering Based Network Traffic Data Reduction for Improving Suspicious Flow Detection[C]//2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). IEEE, 2018: 744-753. https://ieeexplore.ieee.org/document/8455976

DeepGFL: Deep Feature Learning via Graph for Attack Detection on Flow-based Network Traffic DeepGFL: Deep Feature Learning via Graph for Attack Detection on Flow-based Network Traffic

Published in Milcom IEEE, 2018

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Recommended citation: Yepeng Yao, Liya Su, Zhigang Lu: DeepGFL: Deep Feature Learning via Graph for Attack Detection on Flow-based Network Traffic[C]//2018 Milcom. IEEE, 2018: 579-584. https://ieeexplore.ieee.org/document/8599821

A Novel Approach for Identifying Lateral Movement Attacks Based on Network Embedding A Novel Approach for Identifying Lateral Movement Attacks Based on Network Embedding

Published in IEEE International Symposium on Parallel Architectures, Algorithms and Networks (ISPA), 2018

Recommended citation: Mingyi Chen, Yepeng Yao, Junrong Liu, Bo Jiang, Liya Su, Zhigang Lu. A Novel Approach for Identifying Lateral Movement Attacks Based on Network Embedding. ISPA 2018: 708-715.

Marrying Graph Kernel with Deep Neural Network: A Case Study for Network Anomaly Detection Marrying Graph Kernel with Deep Neural Network: A Case Study for Network Anomaly Detection

Published in ICCS Springer, 2019

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Recommended citation: Yepeng Yao, Liya Su, Chen Zhang, Zhigang Lu, Baoxu Liu. Marrying Graph Kernel with Deep Neural Network: A Case Study for Network Anomaly Detection[C]//2019 International Conference on Computational Science. Springer, Cham, 2019: 102-115. https://link.springer.com/chapter/10.1007/978-3-030-22741-8_8

STDeepGraph: Spatial-Temporal Deep Learning on Communication Graphs for Long-Term Network Attack Detection STDeepGraph: Spatial-Temporal Deep Learning on Communication Graphs for Long-Term Network Attack Detection

Published in TrustCom/BigDataSE IEEE, 2019

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Recommended citation: Yepeng Yao, Liya Su, Zhigang Lu, Baoxu Liu. STDeepGraph: Spatial-Temporal Deep Learning on Communication Graphs for Long-Term Network Attack Detection[C]//2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). IEEE, 2019: 120-127. https://ieeexplore.ieee.org/document/8887381

Understanding the Influence of Graph Kernels on Deep Learning Architecture: A Case Study of Flow-Based Network Attack Detection Understanding the Influence of Graph Kernels on Deep Learning Architecture: A Case Study of Flow-Based Network Attack Detection

Published in TrustCom/BigDataSE IEEE, 2019

Download paper here

Recommended citation: Liya Su, Yepeng Yao, Zhigang Lu, Baoxu Liu: Understanding the Influence of Graph Kernels on Deep Learning Architecture: A Case Study of Flow-Based Network Attack Detection[C]//2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). IEEE, 2019: 312-318. https://ieeexplore.ieee.org/abstract/document/8887382

Evil Under the Sun: Understanding and Discovering Attacks on Ethereum Decentralized Applications Evil Under the Sun: Understanding and Discovering Attacks on Ethereum Decentralized Applications

Published in USENIX Security, 2021

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Recommended citation: Liya Su, Xinyue Shen, Xiangyu Du, Xiaojing Liao, XiaoFeng Wang, Luyi Xing, Baoxu Liu. Evil Under the Sun: Understanding and Discovering Attacks on Ethereum Decentralized Applications[C]. USENIX Security. 2021 http://academicpages.github.io/files/evil.pdf

The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks

Published in arXiv, 2023

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Recommended citation: Xiaoyi Chen, Siyuan Tang, Rui Zhu, Shijun Yan, Lei Jin, Zihao Wang, Liya Su, XiaoFeng Wang, Haixu Tang. The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks. arXiv 2023. https://arxiv.org/abs/2311.16189

talks

基于时空上下文信息的复杂恶意行为检测关键技术研究基于时空上下文信息的复杂恶意行为检测关键技术研究

Published: May 12, 2021

Coming soon.

Evil Under the Sun: Understanding and Discovering Attacks on Ethereum Decentralized Applications Evil Under the Sun: Understanding and Discovering Attacks on Ethereum Decentralized Applications

Published: August 01, 2021

I provide a talk on USENIX Security 2021 online about the paper “Evil Under the Sun: Understanding and Discovering Attacks on Ethereum Decentralized Applications”. Here is the talk.

teaching

Teaching experience 1 Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2 Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.

Suliya

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