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Biography
Jason Xue is a Senior Research Scientist (lead of AI Security sub-team) at CSIRO's Data61, Australia. His current research interests are AI security and privacy, system and software security, and Internet measurement. He is the recipient of the ACM SIGSAC Best Paper Award Runner-Up (CCS 2021), two ACM SIGSOFT distinguished paper awards (ASE 2018 and FSE 2023), NDSS distinguished reviewer award (NDSS 2024), ACM SIGSOFT distinguished reviewer award (FSE 2023), Best Student Paper Award, and the IEEE best paper award, and his work has been featured in the mainstream press, including The New York Times, Science Daily, PR Newswire, Yahoo, The Australian Financial Review, and The Courier. He currently serves on the Program Committees of IEEE Symposium on Security and Privacy (Oakland) 2023, ACM CCS 2023, USENIX Security 2023, 2024, NDSS 2023, 2024, ACM/IEEE ICSE 2023, and ACM/IEEE FSE 2023 as well as an area chair of WWW 2024. He is a member of both ACM and IEEE.
Other Interests
Selected Publications:
2024
Shuo Wang, Hongsheng Hu, Jiamin Chang, Benjamin Zi Hao Zhao, Minhui Xue, LACMUS: Latent Concept Masking for General Robustness Enhancement of DNNs, IEEE Symposium on Security and Privacy (Oakland), 2024
Hongsheng Hu, Shuo Wang, Tian Dong, Minhui Xue, Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning, IEEE Symposium on Security and Privacy (Oakland), 2024
Zihan Wang, Zhongkui Ma, Xinguo Feng, Ruoxi Sun, Hu Wang, Minhui Xue, Guangdong Bai, CORELOCKER: Neuron-level Usage Control for AI Models, IEEE Symposium on Security and Privacy (Oakland), 2024
Kai Zhang, Yanjun Zhang, Ruoxi Sun, Pei-Wei Tsai, Muneeb Ul Hassan, Xin Yuan, Minhui Xue, Jinjun Chen, Bounded and Unbiased Composite Differential Privacy, IEEE Symposium on Security and Privacy (Oakland), 2024
Bang Wu, Xingliang Yuan, Shuo Wang, Qi Li, Minhui Xue, Shirui Pan, Securing Graph Neural Networks in MLaaS: A Comprehensive Realization of Query-based Integrity Verification, IEEE Symposium on Security and Privacy (Oakland), 2024
Yansong Gao, Huming Qiu, Zhi Zhang, Binghui Wang, Hua Ma, Alsharif Abuadbba, Minhui Xue, Anmin Fu, Surya Nepal, DeepTheft: Stealing DNN Model Architectures through Power Side Channel, IEEE Symposium on Security and Privacy (Oakland), 2024
Shuo Wang, Hongsheng Hu, Haonan Zhong, Jiamin Chang, Benjamin Zi Hao Zhao, Alfred Chen, Minhui Xue, DNN-GP: Diagnosing and Mitigating Model's Faults Using Latent Concepts, USENIX Security Symposium, 2024
Shuofeng Liu, Zihan, Minhui Xue, Long Wang, Yuanchao Zhang, Guangdong Bai, Being Transparent is Merely the Beginning: Enforcing Purpose Limitation with Polynomial Approximation, USENIX Security Symposium, 2024
Shaofeng Li, Xinyu Wang, Minhui Xue, Haojin Zhu, Zhi Zhang, Yansong Gao, Wen Wu, Xuemin (Sherman) Shen, Yes, One-Bit-Flip Matters! Universal DNN Model Inference Depletion with Runtime Code Fault Injection, USENIX Security Symposium, 2024
Haichen Wang, Shuchao Pang, Zhigang Lu, Yihang Rao, Yongbin Zhou, Minhui Xue, dp-promise: Differentially Private Diffusion Probabilistic Models for Image Synthesis, USENIX Security Symposium, 2024
Hongsheng Hu, Shuo Wang, Jiamin Chang, Haonan Zhong, Ruoxi Sun, Shuang Hao, Haojin Zhu, Minhui Xue, A Duty to Forget, a Right to be Assured? Exposing Vulnerabilities in Machine Unlearning Services, The Network and Distributed System Security (NDSS), 2024
Bang Wu, He Zhang, Xiangwen Yang, Shuo Wang, Minhui Xue, Shirui Pan, Xingliang Yuan, GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks, The Network and Distributed System Security (NDSS), 2024
Kunpeng Zhang, Xiaogang Zhu, Xi Xiao, Minhui Xue, Chao Zhang, Sheng Wen, ShapFuzz: Efficient Fuzzing via Shapley-Guided Byte Selection, The Network and Distributed System Security (NDSS), 2024
Haodong Lu, Dong Gong, Shuo Wang, Minhui Xue, Lina Yao, Kristen Moore, Learning with Mixture of Prototypes for Out-of-Distribution Detection, International Conference on Learning Representations (ICLR), 2024
Zhiyu Zhu, Huaming Chen, Jiayu Zhang, Xinyi Wang, Zhibo Jin, Minhui Xue, Flora D. Salim, AttEXplore: Attribution for Explanation with model parameters eXploration, International Conference on Learning Representations (ICLR), 2024
Longkun Guo, Chaoqi Jia, Kewen Liao, Zhigang Lu, Minhui Xue, Efficient Constrained k-Center Clustering with Background Knowledge, AAAI Conference on Artificial Intelligence (AAAI), 2024
Yuxin Cao, Ziyu Zhao, Xi Xiao, Derui Wang, Minhui Xue, Jin Lu, LogoStyleFool: Vitiating Video Recognition Systems via Logo Style Transfer, AAAI Conference on Artificial Intelligence (AAAI), 2024
Zhiyu Zhu, Huaming Chen, Jiayu Zhang, Xinyi Wang, Zhibo Jin, Minhui Xue, Dongxiao Zhu, Kim-Kwang Raymond Choo, MFABA: A More Faithful and Accelerated Boundary-based Attribution Method for Deep Neural Networks, AAAI Conference on Artificial Intelligence (AAAI), 2024
Nan Wu, Xin Yuan, Shuo Wang, Hongsheng Hu, Minhui Xue, Cardinality Counting in "Alcatraz": A Privacy-aware Federated Learning Approach, The ACM Web Conference (WWW), 2024
Yanjun Zhang, Ruoxi Sun, Liyue Shen, Guangdong Bai, Minhui Xue, Mark Huasong Meng, Xue Li, Ryan Ko, Surya Nepal, Privacy-Preserving and Fairness-Aware Federated Learning for Critical Infrastructure Protection and Resilience, The ACM Web Conference (WWW), 2024
Ziqi Wang, Xiaoyu Xia, Minhui Xue, Ibrahim Khalil, Minghui Liwang, Xun Yi, GEES: Enabling Location Privacy-Preserving Energy Saving in Multi-Access Edge Computing, The ACM Web Conference (WWW), 2024
Zewei Shi, Ruoxi Sun, Jieshan Chen, Jiamou Sun, Minhui Xue, The Invisible Game on the Internet: A Case Study of Decoding Deceptive Patterns, The ACM Web Conference (WWW Short Paper), 2024
Wanlun Ma, Yiliao Song, Minhui Xue, Sheng Wen, Yang Xiang, The “Code” of Ethics: A Holistic Audit of AI Code Generators, IEEE Transactions on Dependable and Secure Computing (TDSC), 2024
2023
Shuo Wang, Sharif Abuadbba, Sidharth Agarwal, Kristen Moore, Ruoxi Sun, Minhui Xue, Surya Nepal, Seyit Camtepe, and Salil Kanhere, PublicCheck: Public Integrity Verification for Services of Run-time Deep Models, IEEE Symposium on Security and Privacy (Oakland), 2023
Yuxin Cao, Xi Xiao, Ruoxi Sun, Derui Wang, Minhui Xue, and Sheng Wen, StyleFool: Fooling Video Classification Systems via Style Transfer, IEEE Symposium on Security and Privacy (Oakland), 2023
Yuxing Zhang, Xiaogang Zhu, Daojing He, Minhui Xue, Shouling Ji, Mohammad Sayad Haghighi, Sheng Wen, and Zhiniang Peng, Detecting Union Type Confusion in Component Object Model, USENIX Security Symposium, 2023
Shuo Wang, Mahathir Almashor, Alsharif Abuadbba, Ruoxi Sun, Minhui Xue, Calvin Wang, Raj Gaire, Seyit Camtepe, and Surya Nepal, DOITRUST: Dissecting On-chain Compromised Internet Domains via Graph Learning, The Network and Distributed System Security (NDSS), 2023
Tian Dong, Shaofeng Li, Guoxing Chen, Minhui Xue, Haojin Zhu, and Zhen Liu, RAI^2: Responsible Identity Audit Governing the Artificial Intelligence, The Network and Distributed System Security (NDSS), 2023
Wanlun Ma, Derui Wang, Ruoxi Sun, Minhui Xue, Sheng Wen, and Yang Xiang, The "Beatrix" Resurrections: Robust Backdoor Detection via Gram Matrices, The Network and Distributed System Security (NDSS), 2023
Chunyi Zhou, Yansong Gao, Anmin Fu, Kai Chen, Zhiyang Dai, Zhi Zhang, Minhui Xue, and Yuqing Zhang, PPA: Preference Profiling Attack Against Federated Learning, The Network and Distributed System Security Symposium (NDSS), 2023
Yuxin Cao, Yian Li, Yumeng Zhu, Derui Wang, Minhui Xue, Flow-Attention-based Spatio-Temporal Aggregation Network for 3D Mask Detection, Conference on Neural Information Processing Systems (NeurIPS), 2023
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, International Conference on Machine Learning (ICML), 2023
Ruoxi Sun, Minhui Xue, Gareth Tyson, Tian Dong, Shaofeng Li, Shuo Wang, Haojin Zhu, Seyit Camtepe, and Surya Nepal, Mate! Are You Really Aware? An Explainability-Guided Testing Framework for Robustness of Malware Detectors, ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2023 (SIGSOFT Distinguished Paper Award)
Yanjun Zhang, Guangdong Bai, Chamikara Mahawaga Arachchige, Mengyao Ma, Liyue Shen, Jingwei Wang, Surya Nepal, Minhui Xue, Long Wang, and Joseph Liu, AgrEvader: Poisoning Membership Inference Against Byzantine-robust Federated Learning, The ACM Web Conference (WWW), 2023
Ruoxi Sun, Minhui Xue, Gareth Tyson, Shuo Wang, Seyit Camtepe, and Surya Nepal, Not Seen, Not Heard in the Digital World! Measuring Privacy Practices in Children’s Apps, The ACM Web Conference (WWW), 2023
Zhiyu Zhu, Huaming Chen, Zhibo Jin, Xinyi Wang, Jiayu Zhang, Minhui Xue, Qinghua Lu, Jun Shen and Kim-Kwang Raymond Choo, FVW: Finding Valuable Weight on Deep Neural Network for Model Pruning, ACM International Conference on Information and Knowledge Management (CIKM), 2023
Haonan Zhong, Jiamin Chang, Ziyue Yang, Tingmin Wu, Pathum Chamikara Mahawaga Arachchige, Chehara Pathmabandu, and Minhui Xue, Copyright Protection and Accountability of Generative AI: Attack, Watermarking and Attribution, The ACM Web Conference (WWW Poster), 2023
Yinshan Li, Hua Ma, Zhi Zhang, Yansong Gao, Alsharif Abuadbba, Minhui Xue, Anmin Fu, Yifeng Zheng, Said F. Al-Sarawi, and Derek Abbott, NTD: Non-Transferability enabled Backdoor Detection, IEEE Transactions on Information Forensics & Security (TIFS), 2023
Aoting Hu, Zhigang Lu, Renjie Xie, and Minhui Xue, VeriDIP: Verifying Ownership of Deep Neural Networks through Privacy Leakage Fingerprints, IEEE Transactions on Dependable and Secure Computing (TDSC), 2023
Hua Ma, Huming Qiu, Yansong Gao, Zhi Zhang, Alsharif Abuadbba, Minhui Xue, Anmin Fu, Zhang Jiliang, Said Al-Sarawi, and Derek Abbott, Quantization Backdoors to Deep Learning Commercial Frameworks, IEEE Transactions on Dependable and Secure Computing (TDSC), 2023
Zihan Wang, Olivia Byrnes, Hu Wang, Ruoxi Sun, Congbo Ma, Huaming Chen, Qi Wu, Minhui Xue, Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography, IEEE Transactions on Computational Social Systems, 2023
2022
Pingyi Hu, Zihan Wang, Ruoxi Sun, Hu Wang, and Minhui Xue, M^4I: Multi-modal Models Membership Inference, Conference on Neural Information Processing Systems (NeurIPS), 2022
Chaoran Li, Xiao Chen, Ruoxi Sun, Minhui Xue, Sheng Wen, Muhammad Ejaz Ahmed, Seyit Camtepe, and Yang Xiang, Cross-Language Android Permission Specification, ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2022
Kunpeng Zhang, Xi Xiao, Xiaogang Zhu, Ruoxi Sun, Minhui Xue, and Sheng Wen, Path Transitions Tell More: Optimizing Fuzzing Schedules via Runtime Program States, ACM International Conference on Software Engineering (ICSE), 2022
Zirui Peng, Shaofeng Li, Guoxing Chen, Cheng Zhang, Haojin Zhu, and Minhui Xue, Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations, Conference on Computer Vision and Pattern Recognition (CVPR), 2022 (Oral)
Bao Gia Doan, Minhui Xue, Shiqing Ma, Ehsan Abbasnejad, and Damith C. Ranasinghe, TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems, IEEE Transactions on Information Forensics & Security (TIFS), 2022
Hamish Spencer, Wei Wang, Ruoxi Sun, and Minhui Xue, Dissecting Malware in the Wild, Australasian Information Security Conference (AISC), 2022 (Best Student Paper Award)
2021
Ruoxi Sun, Wei Wang, Minhui Xue, Gareth Tyson, Seyit Camtepe, and Damith Ranasinghe, An Empirical Assessment of Global COVID-19 Contact Tracing Applications, IEEE International Conference on Software Engineering (ICSE), 2021
Aoting Hu, Renjie Xie, Zhigang Lu, Aiqun Hu, and Minhui Xue, TableGAN-MCA: Evaluating Membership Collisions of GAN-Synthesized Tabular Data Releasing, ACM Conference on Computer and Communications Security (CCS), 2021
Shaofeng Li, Hui Liu, Tian Dong, Benjamin Zi Hao Zhao, Minhui Xue, Haojin Zhu, and Jialiang Lu, Hidden Backdoors in Human-Centric Language Models, ACM Conference on Computer and Communications Security (CCS), 2021 (Best Paper Award Runner-Up)
Tong Zhu, Yan Meng, Haotian Hu, Xiaokuan Zhang, Minhui Xue, and Haojin Zhu, Dissecting Click Fraud Autonomy in the Wild, ACM Conference on Computer and Communications Security (CCS), 2021
Suibin Sun, Le Yu, Xiaokuan Zhang, Minhui Xue, Ren Zhou, Haojin Zhu, Shuang Hao, and Xiaodong Lin, Understanding and Detecting Mobile Ad Fraud Through the Lens of Invalid Traffic, ACM Conference on Computer and Communications Security (CCS), 2021
Xiaotao Feng, Ruoxi Sun, Xiaogang Zhu, Minhui Xue, Sheng Wen, Dongxi Liu, Surya Nepal, and Yang Xiang, SNIPUZZ: Black-box Fuzzing of IoT Firmware via Message Snippet Inference, ACM Conference on Computer and Communications Security (CCS), 2021
Yuantian Miao, Minhui Xue, Chao Chen, Lei Pan, Jun Zhang, Benjamin Zi Hao Zhao, Dali Kaafar, and Yang Xiang, The Audio Auditor: User-Level Membership Inference in Internet of Things Voice Services, Privacy Enhancing Technologies Symposium (PETS), 2021
Jason Ly and Minhui Xue, Poster: Dissecting the Cryptographic Code Exchange, The Network and Distributed System Security Symposium (NDSS), 2021
Jialin Wen, Benjamin Zi Hao Zhao, Minhui Xue, Alina Oprea, and Haifeng Qian, With Great Dispersion Comes Greater Resilience: Efficient Poisoning Attacks and Defenses for Linear Regression Models, IEEE Transactions on Information Forensics & Security (TIFS), 2021
Sen Chen, Lingling Fan, Chunyang Chen, Minhui Xue, Yang Liu, and Lihua Xu, GUI-Squatting Attack: Automated Generation of Android Phishing Apps, IEEE Transactions on Dependable and Secure Computing (TDSC), 2021
2020
Zhushou Tang, Ke Tang, Minhui Xue, Yuan Tian, Sen Chen, Muhammad Ikram, Tielei Wang, and Haojin Zhu, iOS, Your OS, Everybody’s OS: Vetting and Analyzing Network Services of iOS Applications, USENIX Security Symposium, 2020
Sen Chen, Lingling Fan, Guozhu Meng, Ting Su, Minhui Xue, Yinxing Xue, Yang Liu, and Lihua Xu, An Empirical Assessment of Security Risks of Global Android Banking Apps, IEEE International Conference on Software Engineering (ICSE), 2020
Shaofeng Li, Minhui Xue, Benjamin Zi Hao Zhao, Haojin Zhu, and Xinpeng Zhang, Invisible Backdoor Attacks on Deep Neural Networks via Steganography and Regularization, IEEE Transactions on Dependable and Secure Computing (TDSC), 2020
2019
Matthew Joslin, Neng Li, Shuang Hao, Minhui Xue, and Haojin Zhu, Measuring and Analyzing Search Engine Poisoning of Linguistic Collisions, IEEE Symposium on Security and Privacy (Oakland), 2019
Xiaofei Xie, Lei Ma, Felix Juefei-Xu, Minhui Xue, Hongxu Chen, Yang Liu, Jianjun Zhao, Bo Li, Jianxiong Yin, and Simon See, DeepHunter: A Coverage-Guided Fuzz Testing Framework for Deep Neural Networks, 28th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2019
2018
Haizhong Zheng, Minhui Xue, Hao Lu, Shuang Hao, Haojin Zhu, Xiaohui Liang, and Keith Ross, Smoke Screener or Straight Shooter: Detecting Elite Sybil Attacks in User-Review Social Networks, The Network and Distributed System Security Symposium (NDSS), 2018
Lei Ma, Felix Juefei-Xu, Fuyuan Zhang, Jiyuan Sun, Minhui Xue, Bo Li, Chunyang Chen, Ting Su, Li Li, Yang Liu, Jianjun Zhao, and Yadong Wang, DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems, IEEE/ACM International Conference on Automated Software Engineering (ASE), 2018 (Distinguished Paper Award)
2016
Minhui Xue, Cameron L. Ballard, Kelvin Liu, Carson L. Nemelka, Yanqiu Wu, Keith W. Ross, and Haifeng Qian, You Can Yak but You Can’t Hide: Localizing Anonymous Social Network Users, ACM Conference on Internet Measurement Conference (IMC), 2016
Minhui Xue, Gabriel Magno, Evandro Cunha, Virgilio Almeida, and Keith W. Ross, The Right to be Forgotten in the Media: A Data-Driven Study, Proceedings on Privacy Enhancing Technologies (PETS), 2016
Achievements and Awards
-
2024-2024
Distinguished Reviewer Award
Network and Distributed Systems Security (NDSS) Symposium -
2023-2023
Distinguished Paper Award
ACM SIGSOFT ESEC/FSE -
2023-2023
Distinguished Reviewer Award
ACM SIGSOFT ESEC/FSE -
2021-2022
Best Student Paper Award
Australasian Information Security Conference -
2021-2021
Best Paper Award Runner-Up
ACM Conference on Computer and Communications Security (CCS) -
2018-2018
Distinguished Paper Award
ACM SIGSOFT International Conference on Automated Software Engineering (ASE) -
2017-2017
Research Forum Award
Deep Learning Security Workshop (NUS) -
2015-2015
Best Paper Award
IEEE International Symposium on Security and Privacy in Social Networks and Big Data -
2020-2021
Faculty Award of Overall Awesome
The University of Adelaide
Current Roles
-
Senior Research Scientist
Cybersecurity and Quantum Systems Group, CSIRO's Data61
Academic Qualifications
-
2018
PhD – Computer Science (PhD Supervisor: Keith W. Ross)
East China Normal University -
2013
Bachelor of Science – Pure and Applied Mathematics
East China Normal University
Professional Experiences
-
2019-2022
Lecturer (a.k.a. Assistant Professor)
The University of Adelaide -
2018-2019
Postdoctoral Research Fellow
Macquarie University -
2018-2019
Visiting Research Scientist
CSIRO's Data61
Other highlights
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2023-2023
Smart homes, smarter grids: the ‘Internet of Energy’ and the way to net zero, CSIRO News
-
2020-2020
COVIDSafe app best of class for privacy, says study, The Australian Financial Review
-
2020-2020
COVIDSafe app dubbed safest in the world, The Courier
-
2016-2016
Researchers Uncover a Flaw in Europe’s Tough Privacy Rules, The New York Times
-
2016-2016
A Loophole in the Right to Be Forgotten, Columbia Journalism Review
-
2016-2016
Is Anything Ever ‘Forgotten’ Online?, The Conversation
Grants
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2023-2026
Responsible AI Enabling the Internet of Energy, CSIRO – National Science Foundation (US) AI Research Collaboration Program
-
2024-2026
ARC Discovery Project: Rigorous Privacy Compliance in Modern Application Ecosystems
-
2021-2023
ARC Discovery Project: Intelligent Technologies for Smart Cryptography
-
2020-2020
RBlavatnik Interdisciplinary Cyber Research Center, Tel Aviv University, Israel: Leakage-free Cryptography: Eliminating Side Channel Leakage Using Compiler Optimization