Dr Jason Xue
Lecturer
School of Computer Science
Faculty of Sciences, Engineering and Technology
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
-
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
-
Journals
Year Citation 2021 Chan, A., Ma, L., Juefei-Xu, F., Ong, Y. S., Xie, X., Xue, M., & Liu, Y. (2021). Breaking Neural Reasoning Architectures With Metamorphic Relation-Based Adversarial Examples. IEEE Transactions on Neural Networks and Learning Systems, PP, 1-7.
Scopus4 WoS12021 Wen, J., Zhao, B. Z. H., Xue, M., Oprea, A., & Qian, H. (2021). With Great Dispersion Comes Greater Resilience: Efficient Poisoning Attacks and Defenses for Linear Regression Models. IEEE Transactions on Information Forensics and Security, 16, 3709-3723.
Scopus4 WoS12021 Chen, S., Fan, L., Chen, C., Xue, M., Liu, Y., & Xu, L. (2021). GUI-Squatting Attack: Automated Generation of Android Phishing Apps. IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 18(6), 2551-2568.
Scopus4 WoS112019 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.
Scopus7 WoS52018 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.
Scopus7 WoS42018 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.
Scopus120 WoS832017 Xue, M., Yang, L., Ross, K. W., & 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.
Scopus122016 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.
Scopus10 WoS8Sun, R., Wang, W., Dong, T., Li, S., Xue, M., Tyson, G., . . . Nepal, S. (n.d.). Measuring Vulnerabilities of Malware Detectors with
Explainability-Guided Evasion Attacks.Doan, B. G., Xue, M., Ma, S., Abbasnejad, E., & Ranasinghe, D. C. (n.d.). TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep
Neural Network Systems. -
Book Chapters
Year Citation 2022 Li, S., Ma, S., Xue, M., & Zhao, B. Z. H. (2022). Deep Learning Backdoors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13049 LNCS, pp. 313-334). Springer International Publishing.
2013 Szorenyi, A. (2013). Poster. In A. Bartlett, & M. Henderson (Eds.), Things that liberate: an Australian feminist Wunderkammer (pp. 143-148). United Kingdom: Cambridge Scholars Publishing.
-
Conference Papers
Year Citation 2022 Zhang, K., Xiao, X., Zhu, X., Sun, R., Xue, M., & Wen, S. (2022). Path Transitions Tell More: Optimizing Fuzzing Schedules via Runtime Program States. In Proceedings - International Conference on Software Engineering Vol. 2022-May (pp. 1658-1668). ACM.
2022 Spencer, H., Wang, W., Sun, R., & Xue, M. (2022). Dissecting Malware in the Wild. In Proceedings of the ACM International Conference Proceeding Series (ACSW) (pp. 56-64). Virtual Online: Association for Computing Machinery.
Scopus12022 Crawford, M., Wang, W., Sun, R., & Xue, M. (2022). Statically Detecting Adversarial Malware through Randomised Chaining. In Proceedings of the ACM International Conference Proceeding Series (ACSW, 2022) (pp. 91-95). Virtual Online: Association for Computing Machinery.
2021 Chen, L., Wang, H., Zhao, B. Z. H., Xue, M., & Qian, H. (2021). Oriole: Thwarting Privacy Against Trustworthy Deep Learning Models. In Proceedings of the 26th Australasian Conference, (ACISP 2021), as published in Lecture Notes in Computer Science Vol. 13083 (pp. 550-568). Switzerland: Springer International Publishing.
2021 Sun, S., Yu, L., Zhang, X., Xue, M., Zhou, R., Zhu, H., . . . Lin, X. (2021). Understanding and Detecting Mobile Ad Fraud through the Lens of Invalid Traffic. In Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security (CCS '21) (pp. 287-303). virtual online: Association for Computing Machinery.
Scopus22021 Zhu, T., Meng, Y., Hu, H., Zhang, X., Xue, M., & Zhu, H. (2021). Dissecting Click Fraud Autonomy in the Wild. In Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security (CCS '21) (pp. 271-286). New York, NY, United States: Association for Computing Machinery.
2021 Li, S., Liu, H., Dong, T., Zhao, B. Z. H., Xue, M., Zhu, H., & Lu, J. (2021). Hidden Backdoors in Human-Centric Language Models. In Proceedings of the ACM SIGSAC Conference on Computer and Communications Security (ACM SIGSAC 2021) (pp. 3123-3140). New York, USA: ACM.
Scopus52021 Hu, A., Xie, R., Lu, Z., Hu, A., & Xue, M. (2021). TableGAN-MCA: Evaluating Membership Collisions of GAN-Synthesized Tabular Data Releasing. In Proceedings of the ACM Conference on Computer and Communications Security (SIGSAC 2021) (pp. 2096-2112). New York, NY, United States: Association for Computing Machinery (ACM).
Scopus1 WoS12021 Feng, X., Sun, R., Zhu, X., Xue, M., Wen, S., Liu, D., . . . Xiang, Y. (2021). Snipuzz: Black-box Fuzzing of IoT Firmware via Message Snippet Inference. In Proceedings of the 28th ACM SIGSAC Conference on Computer and Communications Security (CCS 2021) (pp. 337-350). Virtual Online: Association for Computing Machinery.
Scopus52021 Sun, R., Wang, W., Xue, M., Tyson, G., Camtepe, S., & Ranasinghe, D. C. (2021). An empirical assessment of global COVID-19 contact tracing applications. In Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering: Companion Proceedings (ICSE-Companion 2021) (pp. 173-174). virtual online: IEEE.
Scopus92021 Xu, J., Xue, M., & Picek, S. (2021). Explainability-based Backdoor Attacks against Graph Neural Networks. In WiseML 2021 - Proceedings of the 3rd ACM Workshop on Wireless Security and Machine Learning (pp. 31-36). New York, NY, United States: Association for Computing Machinery (ACM).
Scopus52021 Sun, R., Wang, W., Xue, M., Tyson, G., Camtepe, S., & Ranasinghe, D. C. (2021). An empirical assessment of global COVID-19 contact tracing applications. In Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering (ICSE 2021) (pp. 1085-1097). online: IEEE.
WoS42020 Sun, R., & Xue, M. (2020). Quality assessment of online automated privacy policy generators: An empirical study. In Proceedings of the 24th Evaluation and Assessment in Software Engineering (EASE 2020) (pp. 270-275). New York: Association for Computing Machinery.
Scopus82020 Wen, J., Zhao, B. Z. H., Xue, M., & Qian, H. (2020). PALOR: Poisoning Attacks Against Logistic Regression. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12248 LNCS (pp. 447-460). Switzerland: Springer Nature.
Scopus12020 Tang, Z., Tang, K., Xue, M., Tian, Y., Chen, S., Ikram, M., . . . Zhu, H. (2020). iOS, your OS, everybody's OS: Vetting and analyzing network services of iOS applications. In Proceedings of the 29th USENIX Security Symposium (pp. 2415-2432). online: USENIX Association.
Scopus4 WoS32020 Wei, W., Sun, R., Xue, M., & Ranasinghe, D. (2020). An automated assessment of android clipboards. In Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering (ASE 2020) (pp. 1249-1251). online: IEEE/ACM.
Scopus1 WoS12020 Sun, R., Wang, W., Xue, M., Tyson, G., & Ranasinghe, D. (2020). VenueTrace: A Privacy-by-Design COVID-19 Digital Contact Tracing Solution. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems, SenSys'20 (pp. 790-791). online: ACM.
Scopus72020 Chen, S., Fan, L., Meng, G., Su, T., Xue, M., Xue, Y., . . . Xu, L. (2020). An empirical assessment of security risks of global android banking apps. In Proceedings of the 42nd International Conference on Software Engineering (ICSE 2020) (pp. 1310-1322). online: Association for Computing Machinery.
Scopus18 WoS152020 Wang, Z., Li, Z., Xue, M., & Tyson, G. (2020). Exploring the Eastern Frontier: A First Look at Mobile App Tracking in China. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12048 LNCS (pp. 314-328). Switzerland: Springer Nature.
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.
Scopus113 WoS962019 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.
Scopus5 WoS32019 Xue, M., Yuan, X., Lee, H., & Ross, K. (2019). Sensing the Chinese diaspora: How mobile apps can provide insights into global migration flows. In IEEE International Conference on Data Mining Workshops, ICDMW Vol. 2019-November (pp. 603-608). online: IEEE.
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.
Scopus62 WoS492019 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.
Scopus22019 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.
Scopus8 WoS52019 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.
Scopus14 WoS112019 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). IEEE.
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.
Scopus72018 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. T. Leavens, A. Garcia, & C. S. 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.
Scopus3 WoS32018 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. T. Leavens, A. Garcia, & C. S. 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.
Scopus25 WoS182018 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.
Scopus236 WoS1872018 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.
Scopus137 WoS992018 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.
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.
Scopus12018 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.
Scopus9 WoS72017 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.
Scopus52017 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.
Scopus5 WoS42016 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.
Scopus12 WoS82016 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.
Scopus109 WoS722016 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.
Scopus13 WoS82016 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.
Scopus132016 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. M. A. Calero, & S. M. 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.
Scopus5 WoS32016 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.
Scopus13 WoS92015 Nemelka, C. L., Ballard, C. L., Liu, K., Xue, M., & Ross, K. W. (2015). You can yak but you can't hide. In COSN 2015 - Proceedings of the 2015 ACM Conference on Online Social Networks (pp. 99). ACM.
Scopus82015 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.
Scopus14 WoS102015 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.
Scopus19 WoS14
- Cybersecurity Fundamentals, Semester 1, 2020
- Software Engineering Workshop, Semester 1, 2020
- Engineering Software as Services II, Semester 2, 2019
- Secure Software Engineering, Semester 2, 2019
-
Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2021 Co-Supervisor Developing a robust distributed multi-agent system for cyber defence Doctor of Philosophy Doctorate Full Time Mr Maxwell James Standen 2020 Co-Supervisor Understanding and Measuring Privacy and Security Assertions of Mobile Apps Doctor of Philosophy Doctorate Full Time Mr Ruoxi Sun -
Past Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2020 - 2022 Co-Supervisor Dissecting Malicious Behaviours of Mobile Applications Master of Philosophy Master Full Time Mr Zach Wang
Connect With Me
External Profiles
