Overview

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I am an Associate Professor in the School of Computing and Information Systems at the University of Melbourne. Before that, I was a faculty member at Monash University. I have broad interests in computer security, including data security and privacy, secure networked system, and trustworthy machine learning. My recent research focus can be found here. I am always looking for self-motivated students. Please email me your CV, transcript, research statement, english test score. Information on UniMelb PhD admission and scholarships can be found here, here, and here.

News

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[Nov'24] Our paper "SIGuard: Guarding Secure Inference with Post Data Privacy" has been accepted by NDSS'25.

[Nov'24] I will co-organise RAID'25 as a general co-chair.

[Oct'24] Our paper "GRID: Protecting training graph from link stealing attacks on GNN models" has been accepted by IEEE S&P'25.

[Jul'24] I am deeply honored to be awarded with an ARC Future Fellowship.

[Jun'24] I have officially joined the University of Melbourne as an Associate Professor.

[Jun'24] I am invited to serve as the TPC member for IEEE S&P'25.

[Apr'24] Our paper "OblivGNN: Oblivious Inference on Transductive and Inductive Graph Neural Network" has been accepted by USENIX Security'24.

[Apr'24] I am invited to serve as the TPC member for NDSS'25.

[Mar'24] Our paper "Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks" has been accepted by IEEE ICDE'24.

[Feb'24] Our paper "Trustworthy Graph Neural Networks: Aspects, Methods and Trends" has been accepted by Proceedings of The IEEE and been featured in the issue cover.

[Nov'23] Our paper "GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks" has been accepted by NDSS'24.

[Oct'23] Our paper "Securing Graph Neural Networks in MLaaS: A Comprehensive Realisation of Query-based Integrity Verification" has been accepted by IEEE S&P'24 (Oakland).

[Oct'23] I am invited to serve as the track co-chair (Security, Privacy, and Trust in Distributed Systems) for IEEE ICDCS'24.

Recent Publications (Selected)

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My full publication list can be found at DBLP and Google Scholar.

• [ACM CCS'23] Lei Xu, Leqian Zheng, Chengzhi Xu, Xingliang Yuan, and Cong Wang, “Leakage-Abuse Attacks Against Forward and Backward Private Searchable Symmetric Encryption”, In the 30th ACM Conference on Computer and Communications Security , Copenhagen, Denmark, 2023 (Acceptance ratio: 19%).
  
  
• [ICML'23] He Zhang, Bang Wu, Shuo Wang, Xiangwen Yang, Minhui Xue, Shirui Pan, and Xingliang Yuan, “Demystifying Uneven Vulnerability of Link Stealing Attacks against Graph Neural Networks”, In the International Conference on Machine Learning, Honolulu, Hawaii, USA, 2023.
  
  
• [ACM WEB'23] Yujin Huang, Terry Yue Zhuo, Qiongkai Xu, Han Hu, Xingliang Yuan, and Chunyang Chen, “Training-free Lexical Backdoor Attacks on Language Models", in the ACM Web Conference, 2023 (Acceptance ratio: 19.9%).
  
  
• [IEEE INFOCOM'22] Yi Liu, Lei Xu, Xingliang Yuan, Cong Wang, and Bo Li, “The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining", in the 41st International Conference on Computer Communications, 2022 (Acceptance ratio: 19.9%).
  
  
• [IEEE TIFS] Xiaoning Liu, Bang Wu, Xingliang Yuan, and Xun Yi, “Leia: A Lightweight Cryptographic Neural Network Inference System at the Edge", IEEE Transactions on Information Forensics and Security, Accepted, 2021.
  
  
• [IEEE TKDE] Viet Vo, Xingliang Yuan, Shi-Feng Sun, Joseph Liu, Surya Nepal, and Cong Wang, “ShieldDB: An Encrypted Document Database with Padding Countermeasures", IEEE Transactions on Knowledge and Data Engineering, Accepted, 2021.
  
  
• [ACM AsiaCCS'22] Bang Wu, Xiangwen Yang, Shirui Pan, and Xingliang Yuan, “Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realisation”, In the 17th ACM ASIA Conference on Computer and Communications Security , 2022 (First round acceptance ratio: 15%).
  
  
• [ESORICS'21] Xiaoning Liu, Yifeng Zheng, Xingliang Yuan, and Xun Yi, “MediSC: Towards Secure and Lightweight Deep Learning as a Medical Diagnostic Service”, In the 26th European Symposium on Research in Computer Security, virtually, 2021 (Best Paper Award, Acceptance ratio: 21%).
  
  
• [IEEE TDSC] Shangqi Lai, Xingliang Yuan, Shi-Feng Sun, Joseph Liu, Ron Steinfeld, Amin Sakzad, and Dongxi Liu, “Practical Encrypted Network Traffic Pattern Matching for Secure Middleboxes”, IEEE Transactions on Dependable and Secure Computing, In Press, 2021.
  
  
• [ISOC NDSS'21] Shangqi Lai, Xingliang Yuan, Joseph Liu, Xun Yi, Qi Li, Dongxi Liu, and Surya Nepal, “OblivSketch: Oblivious Network Measurement as a Cloud Service”, In the Network and Distributed System Security Symposium, virtually, 2021 (Acceptance ratio: 15%).
  
  
• [ACM CCS'19] Huayi Duan, Cong Wang, Xingliang Yuan, Yajin Zhou, Qian Wang, and Kui Ren, “LightBox: Full-stack Protected Stateful Middlebox at Lightning Speed”, in the 26th ACM Conference on Computer and Communications Security, , London, UK, 2019 (Acceptance ratio: 149/933 = 16%).
  
  
• [ACM AsiaCCS'19] Shangqi Lai, Xingliang Yuan, Shi-Feng Sun, Joseph K. Liu, Yuhong Liu, and Dongxi Liu, “GraphSE^2: An Encrypted Graph Database for Privacy-Preserving Social Search”, in the 14th ACM ASIA Conference on Computer and Communications Security , Auckland, New Zealand, 2019 (Acceptance ratio: 44/258 = 17%).
  
  
• [ACM CCS'18] Shi-Feng Sun, Xingliang Yuan, Joseph K. Liu, Ron Steinfeld, Amin Sakzad, Viet Vo, and Surya Nepal, “Practical Backward-Secure Searchable Encryption from Symmetric Puncturable Encryption”, in the 25th ACM Conference on Computer and Communications Security , Toronto, Canada, 2018. (Acceptance ratio: 134/809 = 16.6%).