Minhui Xue (Jason Xue)

Research Fellow

Optus Macquarie University Cyber Security Hub

Macquarie University, Sydney, Australia

 
 

Minhui Xue is currently a Research Fellow with both Optus Macquarie University Cyber Security Hub and CSIRO Data61 at Sydney, Australia. He received his PhD degree at the School of Computer Science and Software Engineering of East China Normal University in June 2018. He received a Bachelor of Science degree in the field of fundamental mathematics from East China Normal University in July 2013, recipient of the Elite Student Scholarship from Fundamental Mathematics Honors Program (National Science Base Class). Previously, he served as a visiting PhD student at the Courant Institute of Mathematical Sciences New York University and Nanyang Technological University, Singapore, as well as a research assistant at New York University Shanghai, advised by Professor Keith W. Ross (NYU). His current research interests are security and privacy, deep learning security and testing, 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 on the shadow program committee of ACM Internet Measurement Conference (IMC 2017), student program committee of the IEEE Symposium on Security and Privacy (Oakland 2017), and currently serves as a reviewer for PETS 2019.

Education and Experience:

  • Research Fellow, Optus Macquarie University Cyber Security Hub, Macquarie University, Sydney, September 2018-Present
  • Visiting Research Fellow, CSIRO Data61, Sydney, October 2018-Present
  • PhD, School of Computer Science and Software Engineering, East China Normal University, September 2013-June 2018
  • Visiting PhD Student, School of Computer Science and Engineering, Nanyang Technological University, Singapore, November 2017-April 2018
  • Visiting PhD Student, Department of Electrical Engineering -- COSIC, Computer Security and Industrial Cryptography, Katholieke Universiteit Leuven (KU Leuven), October 2017
  • Research Assistant, New York University Shanghai, 2014-2017
  • Visiting PhD Student, Department of Computer Science and Engineering, Shanghai Jiao Tong University, 2017
  • Visiting PhD Student, Courant Institute of Mathematical Sciences, New York University, 2016-2017
  • Visiting PhD Student, Tandon School of Engineering, New York University, 2016-2017
  • Teaching Assistant, East China Normal University, 2014
  • Bachelor of Science, Department of Mathematics, East China Normal University, 2009-2013
  • Exchange Student, New York University, 2011
  • Shanghai High School, 2006-2009

Honors & Awards:

  • Extensive Media Coverage (NYT, Science Daily, PR Newswire, EurekAlert!, Yahoo, etc.)
  • ACM SIGSOFT Distinguished Paper Award, 2018
  • Research Forum Award, Deep Learning Security Workshop (DLSRF), 2017
  • Outstanding Graduate Scholarship, East China Normal University, 2016
  • Best Paper Award, IEEE International Symposium on Security and Privacy in Social Networks and Big Data, 2015
  • Full Travel Grant Award, ACM Conference on Online Social Networks, 2015
  • Elite Student Scholarship, International Banco Santander, 2011
  • Elite Student Scholarship, Fundamental Mathematics Honors Program (National Science Base Class of Fundamental Mathematics), 2011
  • Second Prize, National Mathematical Contest in Modeling, 2011

Selected Publications:

  1. 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
  2. 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)
  3. Qingshun Wang, Lintao Gu, Minhui Xue, Lihua Xu, Wenyu Niu, Liang Dou, Liang He, and Tao Xie, FACTS: Automated Black-box Testing of FinTech Systems, ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE), Industry Track, 2018
  4. 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
  5. 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
  6. 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, IEEE Network and Distributed System Security Symposium (NDSS), 2018
  7. 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
  8. Suguo Du, Xiaolong Li, Jinli Zhong, Lu Zhou, Minhui Xue, Haojin Zhu, and Limin Sun, Modeling Privacy Leakage Risks in Large Scale-Social Networks, IEEE Access, 2018
  9. 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)
  10. 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
  11. 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
  12. 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 Internet Measurement Conference (IMC), 2016
  13. Minhui Xue, Gabriel Magno, Evandro Cunha, Virgilio Almeida, and Keith W. Ross, The Right to be Forgotten in the Media: A Data-Driven Study, Privacy Enhancing Technologies (PETS), 2016
  14. 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 (CCS), 2016
  15. Sen Chen, Minhui Xue, and Lihua Xu, Poster: Towards Adversarial Detection of Mobile Malware, ACM International Conference on Mobile Computing and Networking (MobiCom), 2016
  16. Sen Chen, Minhui Xue, Zhushou Tang, Lihua Xu, and Haojin Zhu, StormDroid: A Streaminglized Machine Learning-Based System for Detecting Android Malware, ACM Asia Conference on Computer and Communications Security (AsiaCCS), 2016
  17. Minhui Xue, Limin Yang, Keith W. Ross, and Haifeng Qian, Characterizing User Behaviors in Location-Based Find-and-Flirt Services: Anonymity and Demographics, Peer-to-Peer Networking and Applications (PPNA), 2016
  18. Minhui Xue, Yong Liu, Keith W. Ross, and Haifeng Qian, Thwarting Privacy Protection in Location-Based Social Discovery Services, Security and Communication Networks (SCN), 2016
  19. Minhui Xue, Yong Liu, Keith W. Ross, and Haifeng Qian, I Know Where You Are: Thwarting Privacy Protection in Location-Based Social Discovery Services, INFOCOM Workshop, 2015
  20. Jiawen Peng, Yan Meng, Minhui Xue, Xiaojun Hei, and Keith W. Ross, Attacks and Defenses in Location-Based Social Networks: A Heuristic Number Theory Approach, IEEE International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec), 2015 (Best Paper Award)

Selected Press:

  1. "Researchers Uncover a Flaw in Europe's Tough Privacy Rules", The New York Times, June, 2016
  2. "A Loophole in the Right to Be Forgotten", Columbia Journalism Review, July 2016
  3. "Flaws Found in 'Right To Be Forgotten' Data Privacy Laws", Information Week, July 2016
  4. "Is Anything Ever 'Forgotten' Online?", The Conversation, July 2016
  5. "Weak Spots in Europe's 'Right to be Forgotten' Data Privacy law", Science Daily, June 2016
  6. "NYU Researchers Find Weak Spots in Europe's 'Right to be Forgotten' Data Privacy Law", NYU Newsroom, June 2016
  7. "Computer Science Students to Present at Major Conferences", NYU Shanghai Newsroom, September, 2016
  8. "Cybersecurity does not all Depend on Experts", Wenhui Daily, September, 2016
  9. "Hold That Talk: NYU Researchers Discover Clues For Identifying Yik Yak Users on College Campuses", PR Newswire, October, 2016
  10. "Hold That Talk: NYU Researchers Discover Clues For Identifying Yik Yak Users on College Campuses", Yahoo, October, 2016
  11. "NYU Researchers Discover Clues For Identifying Yik Yak Users on College Campuses", EurekAlert!, October, 2016
  12. "Hold That Talk: NYU Researchers Discover Clues For Identifying Yik Yak Users on College Campuses", NYU Newsroom, October, 2016
  13. "Mining WeChat to Understand the Chinese Diaspora", NYU Center for Data Science, April, 2018

Invited Talks:

  1. "When Software Engineering Meets Cybersecurity and AI", NYU Shanghai, Shanghai, China, 2018
  2. "Data-Driven Analysis of Internet Privacy, Anonymity, and the Law", UT Dallas, Dallas, USA, 2017
  3. "Data-Driven Privacy Analysis of Social Networking", Katholieke Universiteit Leuven (KU Leuven), Brussels, Belgium, 2017
  4. "Data-Driven Analysis of Online Social Networks", Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China, 2017
  5. "You Can Yak but You Can't Hide: Localizing Anonymous Social Network Users", ACM Conference on Internet Measurement Conference (IMC) 2016, Santa Monica, USA
  6. "Poster: Towards Adversarial Detection of Mobile Malware", The 22nd Annual International Conference on Mobile Computing and Networking (MobiCom) 2016, New York, USA
  7. "StormDroid: A Streaminglized Machine Learning-Based System for Detecting Android Malware", ACM Asia Conference on Computer and Communications Security (AsiaCCS) 2016, Xi'an, China
  8. "Data-Driven Privacy Analysis", Zhejiang University, Hangzhou, China, 2016
  9. "You Can Yak but You Can't Hide", ACM Conference on Online Social Networks (COSN) 2015, Stanford University, USA
  10. "I Know Where You Are: Thwarting Privacy Protection in Location-Based Social Discovery Services", INFOCOM Workshop 2015, Hong Kong, China
  11. "Location Privacy: Distance, Countable Set, Convergence", NYU Shanghai, Shanghai, China, 2015

Services:

  • ACM Internet Measurement Conference (IMC) 2017: Shadow Program Committee Member
  • IEEE Symposium on Security and Privacy (Oakland) 2017: Student Program Committee Member
  • IEEE Symposium on Security and Privacy (Oakland) 2019: sub-reviewer
  • USENIX Security Symposium 2018: sub-reviewer
  • IEEE Network and Distributed System Security Symposium (NDSS) 2018, 2019: sub-reviewer
  • Privacy Enhancing Technologies Symposium (PETS) 2016, 2017, 2018, 2019: reviewer

Contact:

Optus Macquarie University Cyber Security Hub

EMC Building, 3 Innovation Road, Level 1 Suite 12, Macquarie University, NSW 2109, Australia

Email: minhuixue@gmail.com or minhui.xue@mq.edu.au