Stacey Truex
PhD Student
Research Interests: Data Privacy, Privacy-Preserving Data Mining, Adversarial Machine Learning
School of Computer Science
Georgia Institute of Technology
Email: staceytruex@gatech.edu
About Me
I am a fifth year PhD student in the School of Computer Science at the Georgia Institute of Technology's College of Computing. I am a graduate researcher in the Distributed Data Intensive Systems Lab directed by Professor Ling Liu where my research focuses on two complementary perspectives: (1) privacy, security, and trust in machine learning models and algorithmic decision making, and (2) secure, privacy-preserving artificial intelligence systems, services, and applications. My PhD research has been generously supported through the IBM PhD Fellowship, the Microsoft Research Women's Fellowship, and the Georgia Tech Presidential, Haley, and Institute for Information Security & Privacy Cybersecurity Fellowships.
Prior to starting at Georgia Tech, I received my Bachelor's degree in Computer Science (B.S.) and Mathematics (B.A.) from Wake Forest University. I then spent some time in industry as a software developer before returning to school at the University of Washington where I received my Master's of Computer Science and Systems. While pursuing my Master's I was also a researcher in the University of Washington Institute of Technology's Center for Data Science as a member of both the Healthcare Analytics and Security research groups.
When I'm not working in the lab you can find me cheering on the New England Patriots or the Wake Forest Demon Deacons or showing off pictures of my adorable dog, Penny, or her predecessor Lincoln.
Selected Publications
- Stacey Truex, Ling Liu, Ka-Ho Chow, Mehmet Emre Gursoy, and Wenqi Wei. "LDP-Fed: Federated Learning with Local Differential Privacy". In: Proceedings of the 3rd International Workshop on Edge Systems, Analytics and Networking. ACM. 2020. [Best Paper Award].
- Vale Tolpegin, Stacey Truex, Mehmet Emre Gursoy, and Ling Yiu. "Data Poisoning Attacks Against Federated Learning Systems". In: Computer Security–ESORICS 2020: 25th European Symposium on Research in Computer Security. 2020.
- Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, and Yanzhao Wu. "A Framework for Evaluating Gradient Leakage Attacks in Federated Learning". In: Computer Security–ESORICS 2020: 25th European Symposium on Research in Computer Security. 2020.
- Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, and Yanzhao Wu. "Understanding Object Detection Through An Adversarial Lens". In: Computer Security–ESORICS 2020: 25th European Symposium on Research in Computer Security. 2020.
- Zheng Chai, Ahsan Ali, Syed Zawad, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, and Yue Cheng. "TiFL: A Tier-based Federated Learning System". In: Proceedings of the 28th International Symposium on High Performance Parallel and Distributed Computing. ACM. 2020.
- ZWenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, and Yanzhao Wu. "“Cross-layer strategic ensemble defense against adversarial examples". In: 2020 International Conference on Computing, Networking and Communications (ICNC). IEEE. 2020, pp.456-460.
- Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Lei Yu, and Wenqi Wei. "Effects of Differential Privacy and Data Skewedness on Membership Inference Vulnerability". In: IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications. IEEE. 2019.
- Stacey Truex, Nathalie Baracaldo, Ali Anwar, Heiko Ludwig, Thomas Steinke, Rui Zhang, and Yi Zhou. "A Hybrid Approach to Privacy-Preserving Federated Learning". In: Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security. ACM. 2019. [Best Paper Award]
- Mehmet Emre Gursoy, Acar Tamersoy, Stacey Truex, Wenqi Wei, and Ling Liu. "Security and Utility-Aware Data Collection with Condensed Local Differential Privacy". In: IEEE Transactions on Dependable and Secure Computing (2019).
- Ling Liu, Wenqi Wei, Ka-Ho Chow, Margaret Loper, Mehmet Emre Gursoy, Stacey Truex, and Yanzhao Wu. "Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness". In: 2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS). IEEE. 2019.
- Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Lei Yu, and Wenqi Wei. "Towards Demystifying Membership Inference Attacks". In: IEEE Transactions on Services Computing. IEEE. 2019.
- Lei Yu, Ling Liu, Calton Pu, Mehmet Emre Gursoy, and Stacey Truex. "Differentially Private Model Publishing for Deep Learning". In: Proceedings of the 40th IEEE Symposium on Security and Privacy (Oakland). IEEE. 2019.
- Mehmet Emre Gursoy, Ling Liu, Stacey Truex, Lei Yu, and Wenqi Wei. "Utility-aware Synthesis of Differentially Private and Attack-Resilient Location Traces". In: Proceedings of the 25th ACM Conference on Computer and Communications Security (CCS). ACM. 2018.
- Mehmet Emre Gursoy, Ling Liu, Stacey Truex, and Lei Yu. "Differentially private and utility preserving publication of trajectory data". In: IEEE Transactions on Mobile Computing. IEEE. 2018.
- Stacey Truex, Ling Liu, Mehmet Emre Gursoy, and Lei Yu. "Privacy-Preserving Inductive Learning with Decision Trees". In: Big Data (BigData Congress), 2017 IEEE International Congress on (pp. 57-64). IEEE.
- De Cock, Martine, Rafael Dowsley, Caleb Horst, Raj Katti, Anderson Nascimento, Wing-Sea Poon, and Stacey Truex. "Efficient and Private Scoring of Decision Trees, Support Vector Machines and Logistic Regression Models based on Pre-Computation." In: IEEE Transactions on Dependable and Secure Computing (2017).
- De Cock, Martine, Rafael Dowsley, Anderson CA Nascimento, and Stacey C Newman. "Fast, Privacy Preserving Linear Regression over Distributed Datasets based on Pre-Distributed Data". In: Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security. ACM, pp. 3-14.
- Basu Roy, Senjuti, Ankur Teredesai, Kiyana Zolfaghar, Rui Liu, David Hazel, Stacey Newman, and Albert Marinez. "Dynamic Hierarchical Classification for Patient Risk-of-Readmission". In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, pp. 1691-1700.
Presentations
- LDP-Fed: Federated Learning with Local Differential Privacy. Slides.
- Effects of Differential Privacy & Data Skewness on Membership Inference. Slides.
- Exposing Membership Inference Vulnerability & Mitigation Effectiveness. Poster.
- Privacy-Preserving Decision Tree Learning: Evaluation to Collaboration. Poster.
- Trust and Privacy in Big Data Driven Machine Learning Algorithms. Poster.
- Privacy-Preserving Decision Tree Ensembles. Poster.
- Privacy-Preserving Inductive Learning with Decision Trees. Slides.
- Private Predictive Modeling Power. Video.
Fellowships & Awards
- IBM PhD Fellow, 2019-2021
- Georgia Institute of Technology Presidential Fellow, 2016-2020
- Georgia Institute of Technology Haley Fellow, 2019-2020
- IEEE TPS Student Travel Award, 2019
- ACM FAT* Conference Scholarship Award, 2019
- Georgia Institute of Technology's Institute for Information Security & Privacy
Cybersecurity Fellow, Spring 2017 - Microsoft Research Women's Fellow, 2016-2017
- NCWIT Collegiate Award Honorable Mention, 2017
- Women in CyberSecurity Conference Student Scholarship, 2018
- NDSS Student Travel Grant, 2017
- CRA-W Graduate Cohort, 2017
- Grace Hopper Scholarship, 2010 and 2016
- KDD Student Travel Award, 2015
Contact Information
School of Computer Science College of Computing Georgia Institute of TechnologyDistributed Data Intensive Systems Lab Klaus Advanced Computing Building, Room 3319 266 Ferst Drive Atlanta, GA 30313
Email: staceytruex@gatech.edu