Dr Jason Xue

Dr Jason Xue
 Position Lecturer
 Org Unit School of Computer Science
 Email jason.xue@adelaide.edu.au
 Telephone +61 4 2037 8228
 Mobile +61 4 2037 8228
 Location Floor/Room 4 16 ,  Ingkarni Wardli ,   North Terrace
  • Biography/ Background

    Bio Sketch:

    Minhui Xue is (continuing) Lecturer (a.k.a. Assistant Professor) of School of Computer Science at the University of Adelaide. He is also Honorary Lecturer with Macquarie University. Previously, he was Research Fellow with Macquarie University and a visiting research scientist at CSIRO-Data61 at Sydney, Australia. His current research interests are machine learning security and privacy, system and software security, and Internet measurement. He is the recipient of the ACM SIGSOFT distinguished paper award and IEEE best paper award, and his work has been featured in the mainstream press, including The New York Times, Science Daily, PR Newswire, and Yahoo. He was the PC chair of the 1st IEEE AI4MOBILE workshop, and currently co-chairs the 1st IEEE MASS workshop on Smart City Security and Privacy as well as serves on the PC committee of PETS 2020.


    • PhD – Computer Science, East China Normal University and NYU Shanghai, 2013 - 2018, PhD Advisor: Keith W. Ross
    • Bachelor of Science – Pure and Applied Mathematics, East China Normal University, 2009 - 2013


    • Research Fellow, Macquarie University, 2018 - 2019
    • Visiting Research Scientist, CSIRO-Data61, 2018 - 2019                                                                        
    • Visiting PhD Student, Nanyang Technological University (NTU), 2017 - 2018
    • Visiting PhD Student, Katholieke Universiteit Leuven (KU Leuven), 2017                                                    
    • Visiting PhD Student, Shanghai Jiao Tong University, 2017                                                                               
    • Visiting PhD Student, Courant Institute of Mathematical Sciences, New York University, 2016 - 2017
    • Visiting Student, New York University, 2012

  • Awards & Achievements


    • ACM SIGSOFT Distinguished Paper Award, 2018                                                  
    • Research Forum Award, Deep Learning Security Workshop (NUS), 2017
    • Best Paper Award, IEEE International Symposium on Security and Privacy in Social Networks and Big Data, 2015

    Selected Press:

    • Researchers Uncover a Flaw in Europe’s Tough Privacy Rules, The New York Times, June, 2016
    • A Loophole in the Right to Be Forgotten, Columbia Journalism Review, July 2016
    • Flaws Found in ‘Right To Be Forgotten’ Data Privacy Laws, Information Week, July 2016
    • Is Anything Ever ‘Forgotten’ Online?, The Conversation, July 2016
    • Weak Spots in Europe’s ‘Right to be Forgotten’ Data Privacy law, Science Daily, June 2016
    • NYU Researchers Find Weak Spots in Europe’s ‘Right to be Forgotten’ Data Privacy Law, NYU Newsroom, June 2016
    • Hold That Talk: NYU Researchers Discover Clues For Identifying Yik Yak Users on College Campuses, PR Newswire, ACM TechNews, Yahoo, October, 2016
    • Yik Yak Could Lose Anonymity, Washington Square News, October, 2016
    • Mining WeChat to Understand the Chinese Diaspora, NYU Center for Data Science, April, 2018 
  • Research Interests

    • Machine Learning Security and Privacy
    • System and Software Security
    • Internet Measurement and Fraud Detection

  • Publications


    • 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
    • Minhui Xue, Xin Yuan, Heather Lee, and Keith Ross, Sensing the Chinese Diaspora: How Mobile Apps Can Provide Insights into Global Migration Flows, IEEE International Conference on Data Mining (ICDM) Workshop, 2019
    • Qingrong Chen, Chong Xiang, Minhui Xue, Bo Li, Nikita Borisov, Dali Kaafar, and Haojin Zhu, Differentially Private Data Sharing: Sharing Models versus Sharing Data, ACM Conference on Computer and Communications Security (CCS) Workshop, 2019
    • Yuantian Miao, Ben Zi Hao Zhao, Minhui Xue, Chao Chen, Lei Pan, Jun Zhang, Dali Kaafar, and Yang Xiang, The Audio Auditor: Participant-Level Membership Inference in Internet of Things Voice Services, ACM Conference on Computer and Communications Security (CCS) Workshop, 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
    • Chong Xiang, Xinyu Wang, Qingrong Chen, Minhui Xue, Zhaoyu Gao, Haojin Zhu, Cailian Chen, and Qiuhua Fan, No-Jump-into-Latency in China’s Internet! Toward Last-Mile Hop Count Based IP-Geolocalization, IEEE/ACM International Symposium on Quality of Service (IWQoS), 2019
    • Shaofeng Li, Benjamin Zi Hao Zhao, Jiahao Yu, Minhui Xue, Dali Kaafar, and Haojin Zhu, Invisible Backdoor Attacks Against Deep Neural Networks (https://arxiv.org/abs/1909.02742)


    • 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)
    • Qingshun Wang, Lintao Gu, Minhui Xue, Lihua Xu, Wenyu Niu, Liang Dou, Liang He, Tao Xie, FACTS: Automated Comprehensive Testing of FinTech Systems, ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE), Industry Track, 2018
    • Sen Chen, Ting Su, Lingling Fan, Guozhu Meng, Minhui Xue, Yang Liu, and Lihua Xu. Are Mobile Banking Apps Secure? What Can be Improved?, ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE), Industry Track, 2018
    • Lei Ma, Fuyuan Zhang, Jiyuan Sun, Minhui Xue, Bo Li, Felix Juefei-Xu, Chao Xie, Li Li, Yang Liu, Jianjun Zhao, and Yadong Wang, DeepMutation: Mutation Testing of Deep Learning Systems, IEEE International Symposium on Software Reliability Engineering (ISSRE), 2018
    • Zhushou Tang, Minhui Xue, Guozhu Meng, Chengguo Ying, Yugeng Liu, Yangyang Li, Haojin Zhu, and Yang Liu, Securing Android Applications via Edge Assistant Third-Party Library Detection, Elsevier Computers & Security, 2018 


    • Wenqi Bu, Minhui Xue, Lihua Xu, Yajin Zhou, Zhushou Tang, and Tao Xie, When Program Analysis Meets Mobile Security: An Industrial Study of Misusing Android Internet Sockets, ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE), Industry Track, 2017
    • Sen Chen, Minhui Xue, Lingling Fan, Shuang Hao, Lihua Xu, Haojin Zhu, and Bo Li, Automated Poisoning Attacks and Defenses in Malware Detection Systems: An Adversarial Machine Learning Approach, Elsevier Computers & Security, 2017
    • Qingrong Chen, Minhui Xue, Chong Xiang, Bo Li, Haizhong Zheng, and Haojin Zhu, Do We Need Original Data for Training? Toward Designing Privacy-Preserving Machine Learning, Deep Learning Security Workshop (DLSRF), 2017 (Research Forum Award)

    • 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
    • Lingling Fan, Minhui Xue, Sen Chen, Lihua Xu, and Haojin Zhu, POSTER: Accuracy vs. Time Cost: Detecting Android Malware through Pareto Ensemble Pruning, ACM Conference on Computer and Communications Security 2016 (CCS), 2016
    • Sen Chen, Minhui Xue, and Lihua Xu, Poster: Towards Adversarial Detection of Mobile Malware, ACM International Conference on Mobile Computing and Networking (MobiCom), 2016
    • Sen Chen, Minhui Xue, Zhushou Tang, Lihua Xu, and Haojin Zhu, StormDroid: A Streaminglized Machine Learning-Based System for Detecting Android Malware, ACM on Asia Conference on Computer and Communications Security (AsiaCCS), 2016
    • Minhui Xue, Yong Liu, Keith W. Ross, and Haifeng Qian, Thwarting Privacy Protection in Location-Based Social Discovery Services, Security and Communication Networks, 2016

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Entry last updated: Monday, 9 Sep 2019

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