Jason Xue

Dr Jason Xue

Lecturer

School of Computer Science

Faculty of Engineering, Computer and Mathematical Sciences

Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.


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.

Research Interests:

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

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 
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  • Appointments

    Date Position Institution name
    2019 - 2019 Visiting Research Scientist Commonwealth Scientific and Industrial Research Organisation
    2018 - 2019 Research Fellow Macquarie University
    2017 - 2018 Visiting PhD Student Nanyang Technological University
    2016 - 2017 Visiting PhD Student New York University
    2013 - 2018 Visiting PhD Student New York University Shanghai
  • Awards and Achievements

    Date Type Title Institution Name Country Amount
    2018 Award ACM SIGSOFT Distinguished Paper Award ACM SIGSOFT United States
    2017 Award Research Forum Award National University of Singapore Singapore
    2015 Award Best Paper Award IEEE International Symposium on Security and Privacy in Social Networks and Big Data United States
  • Language Competencies

    Language Competency
    Chinese (Mandarin) Can read, write, speak, understand spoken and peer review
    English Can read, write, speak, understand spoken and peer review
  • Education

    Date Institution name Country Title
    2013 - 2018 East China Normal University and NYU Shanghai China PhD - Computer Science
    2009 - 2013 East China Normal University China Bachelor of Science – Pure and Applied Mathematics
  • Research Interests

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  • Journals

    Year Citation
    2019 Tang, Z., Xue, M., Meng, G., Ying, C., Liu, Y., He, J., . . . Liu, Y. (2019). Securing android applications via edge assistant third-party library detection. Computers and Security, 80, 257-272.
    DOI
    2018 Du, S., Li, X., Zhong, J., Zhou, L., Xue, M., Zhu, H., & Sun, L. (2018). Modeling Privacy Leakage Risks in Large-Scale Social Networks. IEEE Access, 6, 17653-17665.
    DOI Scopus2
    2018 Chen, S., Xue, M., Fan, L., Hao, S., Xu, L., Zhu, H., & Li, B. (2018). Automated poisoning attacks and defenses in malware detection systems: An adversarial machine learning approach. Computers and Security, 73, 326-344.
    DOI Scopus21 WoS11
    2017 Xue, M., Yang, L., Ross, K., & Qian, H. (2017). Characterizing user behaviors in location-based find-and-flirt services: Anonymity and demographics: A WeChat Case Study. Peer-to-Peer Networking and Applications, 10(2), 357-367.
    DOI Scopus5
    2016 Xue, M., Liu, Y., Ross, K., & Qian, H. (2016). Thwarting location privacy protection in location-based social discovery services. Security and Communication Networks, 9(11), 1496-1508.
    DOI Scopus6 WoS4
  • Conference Papers

    Year Citation
    2019 Xiang, C., Wang, X., Chen, Q., Xue, M., Gao, Z., Zhu, H., . . . Fan, Q. (2019). No-jump-into-latency in China's internet! Toward last-mile hop count based IP geo-localization. In Proceedings of the International Symposium on Quality of Service, IWQoS 2019 (pp. 1-10). online: ACM.
    DOI
    2019 Ma, L., Juefei-Xu, F., Xue, M., Li, B., Li, L., Liu, Y., & Zhao, J. (2019). DeepCT: Tomographic Combinatorial Testing for Deep Learning Systems. In X. Wang, D. Lo, & E. Shihab (Eds.), SANER 2019, Proceedings of the 2019 IEEE 26th International Conference on Software Analysis, Evolution, and Reengineering (pp. 614-618). online: IEEE.
    DOI Scopus3 WoS1
    2019 Chen, S., Xue, M., Fan, L., Ma, L., Liu, Y., & Xu, L. (2019). How Can We Craft Large-Scale Android Malware? An Automated Poisoning Attack. In Y. Liu, L. Ma, L. Li, & M. Xue (Eds.), AI4Mobile 2019 - 2019 IEEE 1st International Workshop on Artificial Intelligence for Mobile (pp. 21-24). online: IEEE.
    DOI Scopus1 WoS1
    2019 Shahpasand, M., Hamey, L., Vatsalan, D., & Xue, M. (2019). Adversarial Attacks on Mobile Malware Detection. In Y. Liu, L. Ma, L. Li, & M. Xue (Eds.), AI4Mobile 2019 - 2019 IEEE 1st International Workshop on Artificial Intelligence for Mobile (pp. 17-20). online: IEEE.
    DOI
    2019 Liu, Y., Ma, L., Li, L., & Xue, M. (2019). Message from the Chairs: IEEE International Workshop on Artificial Intelligence for Mobile. In AI4Mobile 2019 - 2019 IEEE 1st International Workshop on Artificial Intelligence for Mobile (pp. III).
    DOI
    2019 Xie, X., Ma, L., Juefei-Xu, F., Xue, M., Chen, H., Liu, Y., . . . See, S. (2019). Deephunter: A coverage-guided fuzz testing framework for deep neural networks. In ISSTA 2019 - Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis (pp. 158-168). online: ACM.
    DOI Scopus3
    2019 Joslin, M., Li, N., Hao, S., Xue, M., & Zhu, H. (2019). Measuring and analyzing search engine poisoning of linguistic collisions. In Proceedings - IEEE Symposium on Security and Privacy Vol. 2019-May (pp. 1311-1325). online: IEEE.
    DOI
    2018 Zheng, H., Li, N., Xue, M., Du, S., & Zhu, H. (2018). Fake reviews tell no tales? Dissecting click farming in content-generated social networks. In 2017 IEEE/CIC International Conference on Communications in China (ICCC) Vol. 2018-January (pp. 1-6). Qingdao, China: IEEE.
    DOI
    2018 Li, N., Du, S., Zheng, H., Xue, M., & Zhu, H. (2018). Fake reviews tell no tales? Dissecting click farming in content-generated social networks. In China Communications Vol. 15 (pp. 98-109). Qingdao, China: IEEE.
    DOI Scopus1 WoS1
    2018 Xiang, C., Chen, Q., Xue, M., & Zhu, H. (2018). APPCLASSIFIER: Automated App Inference on Encrypted Traffic via Meta Data Analysis. In 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings (pp. 1-7). online: IEEE.
    DOI Scopus1
    2018 Wang, Q., Gu, L., Xue, M., Xu, L., Niu, W., Dou, L., . . . Xie, T. (2018). FACTS: Automated black-box testing of fintech systems. In G. Leavens, A. Garcia, & C. Pasareanu (Eds.), ESEC/FSE 2018 - Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp. 839-844). Online: ASSOC COMPUTING MACHINERY.
    DOI Scopus1 WoS1
    2018 Chen, S., Su, T., Fan, L., Meng, G., Xue, M., Liu, Y., & Xu, L. (2018). Are mobile banking apps secure? what can be improved?. In G. Leavens, A. Garcia, & C. Pasareanu (Eds.), ESEC/FSE 2018 - Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp. 797-802). online: ASSOC COMPUTING MACHINERY.
    DOI Scopus5 WoS1
    2018 Ma, L., Juefei-Xu, F., Zhang, F., Sun, J., Xue, M., Li, B., . . . Wang, Y. (2018). DeepGauge: Multi-granularity testing criteria for deep learning systems. In ASE 2018 - Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering (pp. 120-131). Online: Association for computing Machinery Inc.
    DOI Scopus24
    2018 Ma, L., Zhang, F., Sun, J., Xue, M., Li, B., Juefei-Xu, F., . . . Wang, Y. (2018). DeepMutation: Mutation Testing of Deep Learning Systems. In S. Ghosh, R. Natella, B. Cukic, R. Poston, & N. Laranjeiro (Eds.), Proceedings of the International Symposium on Software Reliability Engineering, ISSRE Vol. 2018-October (pp. 100-111). online: IEEE.
    DOI Scopus14 WoS4
    2018 Hou, J., Xue, M., & Qian, H. (2018). Unleash the power for tensor: A hybrid malware detection system using ensemble classifiers. In G. Wang, G. Fox, G. Martinez, R. Hill, & P. Mueller (Eds.), Proceedings of the 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017 (pp. 1130-1137). online: IEEE.
    DOI
    2017 Wang, J., Cheng, H., Xue, M., & Hei, X. (2017). Revisiting localization attacks in mobile app people-nearby services. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10656 LNCS (pp. 17-30). Switzerland: Springer.
    DOI
    2017 Bu, W., Xue, M., Xu, L., Zhou, Y., Tang, Z., & Xie, T. (2017). When program analysis meets mobile security: An industrial study of misusing android internet sockets. In E. Bodden, W. Schafer, A. VanDeursen, & A. Zisman (Eds.), Proceedings of the ACM SIGSOFT Symposium on the Foundations of Software Engineering Vol. Part F130154 (pp. 842-847). Online: ASSOC COMPUTING MACHINERY.
    DOI Scopus2 WoS2
    2016 Chen, S., Xue, M., & Xu, L. (2016). Poster: Towards adversarial detection of mobile malware. In Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM Vol. 0 (pp. 415-416). New York City, NY: ASSOC COMPUTING MACHINERY.
    DOI Scopus6 WoS3
    2016 Chen, S., Xue, M., Tang, Z., Xu, L., & Zhu, H. (2016). StormDroid: A streaminglized machine learning-based system for detecting android malware. In ASIA CCS 2016 - Proceedings of the 11th ACM Asia Conference on Computer and Communications Security (pp. 377-388). online: ASSOC COMPUTING MACHINERY.
    DOI Scopus42 WoS21
    2016 Peng, J., Meng, Y., Xue, M., Hei, X., & Ross, K. (2016). Attacks and defenses in location-based social networks: A heuristic number theory approach. In Proceedings of the 2015 International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2015 (pp. 64-71). online: IEEE.
    DOI Scopus8 WoS3
    2016 Xue, M., Ballard, C., Liu, K., Nemelka, C., Wu, Y., Ross, K., & Qian, H. (2016). You can yak but you can't hide: Localizing anonymous social network users. In Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC Vol. 14-16-November-2016 (pp. 25-31). online: ACM.
    DOI Scopus11
    2016 Cheng, H., Mao, S., Xue, M., & Hei, X. (2016). On the impact of location errors on localization attacks in location-based social network services. In G. Wang, I. Ray, J. Calero, & S. Thampi (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10066 LNCS (pp. 343-357). Online: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus3 WoS1
    2016 Fan, L., Xue, M., Chen, S., Xu, L., & Zhu, H. (2016). POSTER: Accuracy vs. time cost: Detecting android malware through Pareto ensemble pruning. In Proceedings of the ACM Conference on Computer and Communications Security Vol. 24-28-October-2016 (pp. 1748-1750). Vienna, AUSTRIA: ASSOC COMPUTING MACHINERY.
    DOI Scopus8 WoS3
    2015 Nemelka, C., Ballard, C., Liu, K., Xue, M., & Ross, K. (2015). You can yak but you can't hide. In COSN 2015 - Proceedings of the 2015 ACM Conference on Online Social Networks (pp. 99).
    DOI Scopus5
    2015 Wang, R., Xue, M., Liu, K., & Qian, H. (2015). Data-driven privacy analytics: A wechat case study in location-based social networks. In K. Xu, & H. Zhu (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9204 (pp. 561-570). Online: SPRINGER-VERLAG BERLIN.
    DOI Scopus7 WoS5
    2015 Xue, M., Liu, Y., Ross, K., & Qian, H. (2015). I know where you are: Thwarting privacy protection in location-based social discovery services. In Proceedings of the 2015 IEEE Conference on Computer Communications Workshops (INFOCOM) Vol. 2015-August (pp. 179-184). online: IEEE.
    DOI Scopus12 WoS9
  • Engineering Software as Services II, Semester 2, 2019
  • Secure Software Engineering, Semester 2, 2019
  • Position: Lecturer
  • Phone: 0420378228
  • Email: jason.xue@adelaide.edu.au
  • Campus: North Terrace
  • Building: Ingkarni Wardli, floor 4
  • Room: 4 16
  • Org Unit: School of Computer Science

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