Research

My research interests include:

  • Data privacy and security
  • Cybersecurity
  • Data analytics and mining
  • Security and privacy in machine learning (ML) and artificial intelligence (AI)
  • Adversarial machine learning
  • Internet of Things

My publications are listed below and on my Google Scholar profile.

Journal Publications

  1. M.E. Gursoy, A. Tamersoy, S. Truex, W. Wei, and L. Liu. “Secure and utility-aware data collection with condensed local differential privacy”. IEEE Transactions on Dependable and Secure Computing (TDSC). [pdf]
  2. S. Truex, L. Liu, M.E. Gursoy, L. Yu, and W. Wei. “Demystifying membership inference attacks in machine learning as a service”. IEEE Transactions on Services Computing (TSC). [pdf]
  3. M.E. Gursoy, L. Liu, S. Truex, and L. Yu. “Differentially private and utility-preserving publication of trajectory data”. IEEE Transactions on Mobile Computing (TMC). [pdf]
  4. A. Inan, M.E. Gursoy, and Y. Saygin. “Sensitivity analysis for non-interactive differential privacy: bounds and efficient algorithms”. IEEE Transactions on Dependable and Secure Computing (TDSC). [pdf]
  5. E. Kaplan, M.E. Gursoy, M.E. Nergiz, and Y. Saygin. “Known sample attacks on relation preserving data transformations”. IEEE Transactions on Dependable and Secure Computing (TDSC). [pdf]
  6. M.E. Gursoy, A. Inan, M.E. Nergiz, and Y. Saygin. “Differentially private nearest neighbor classification”. Data Mining and Knowledge Discovery, 31 (5), 1544-1575. [pdf]
  7. E. Kaplan, M.E. Gursoy, M.E. Nergiz, and Y. Saygin. “Location disclosure risks of releasing trajectory distances”. Data and Knowledge Engineering (DKE). [pdf]
  8. M.E. Gursoy, A. Inan, M.E. Nergiz, and Y. Saygin. “Privacy-preserving learning analytics: challenges and techniques”. IEEE Transactions on Learning Technologies (TLT), 10 (1), 68-81. [pdf]
  9. I. Ozalp, M.E. Gursoy, M.E. Nergiz, and Y. Saygin. “Privacy-preserving publishing of hierarchical data”. ACM Transactions on Privacy and Security (TOPS), 19 (3), 7. [pdf]

Conference and Workshop Publications

  1. M.E. Gursoy, V. Rajasekar, and L. Liu. “Utility-optimized synthesis of differentially private location traces”. 2020 IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS 2020). [pdf]
  2. V. Tolpegin, S. Truex, M.E. Gursoy, and L. Liu. “Data poisoning attacks against federated learning systems”. 25th European Symposium on Research in Computer Security (ESORICS 2020). [pdf] Acceptance rate: 19.6%
  3. W. Wei, L. Liu, M. Loper, K-H. Chow, M.E. Gursoy, S. Truex, and Y. Wu. “A framework for evaluating client privacy leakages in federated learning”. 25th European Symposium on Research in Computer Security (ESORICS 2020). [pdf] Acceptance rate: 19.6%
  4. K-H. Chow, L. Liu, M.E. Gursoy, S. Truex, W. Wei, and Y. Wu. “Understanding object detection through an adversarial lens”. 25th European Symposium on Research in Computer Security (ESORICS 2020). [pdf] Acceptance rate: 19.6%
  5. S. Truex, L. Liu, K-H. Chow, M.E. Gursoy, and W. Wei. “LDP-Fed: Federated learning with local differential privacy”. 2020 ACM International Workshop on Edge Systems, Analytics and Networking (EdgeSys 2020). [pdf] Best Paper Award!
  6. W. Wei, L. Liu, M. Loper, K-H. Chow, M.E. Gursoy, S. Truex, and Y. Wu. “Cross-layer strategic ensemble defense against adversarial examples”. 2020 International Conference on Computing, Networking and Communications (ICNC 2020). [pdf]
  7. S. Truex, L. Liu, M.E. Gursoy, W. Wei, and L. Yu. “Effects of differential privacy and data skewness on membership inference vulnerability”. 2019 IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS 2019). [pdf]
  8. L. Yu, L. Liu, C. Pu, K-H. Chow, M.E. Gursoy, S. Truex, H. Min, A. Iyengar, G. Su, Q. Zhang, and D. Dillenberger. “GRAHIES: Multi-scale graph representation learning with latent hierarchical structure”. 2019 IEEE International Conference on Cognitive Machine Intelligence (CogMI 2019). [pdf]
  9. V. Krishnamurthy, K. Nezafati, J. Bae, M.E. Gursoy, M. Zhong, and V. Singh. “Classification of driving behavior events utilizing kinematic classification and machine learning for down sampled time series data”. 2019 International Workshop in Big Data for Intelligent Transportation Systems (BITS 2019). [pdf]
  10. L. Liu, W. Wei, K-H. Chow, M. Loper, M.E. Gursoy, S. Truex, and Y. Wu. “Deep neural network ensembles against deception: ensemble diversity, accuracy and robustness”. 2019 IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS 2019). [pdf]
  11. L. Yu, L. Liu, C. Pu, M.E. Gursoy, and S. Truex. “Differentially private model publishing for deep learning”. 2019 IEEE Symposium on Security and Privacy (S&P 2019). [pdf] Acceptance rate: 12%
  12. M.E. Gursoy, L. Liu, S. Truex, L. Yu, and W. Wei. “Utility-aware synthesis of differentially private and attack-resilient location traces”. 2018 ACM Conference on Computer and Communications Security (CCS 2018). [pdf] Acceptance rate: 16.6%
  13. E. Yigitoglu, M.E. Gursoy, L. Liu, M. Loper, B. Bamba, and K. Lee. “PrivacyZone: A novel approach to protecting location privacy of mobile users”. 2018 IEEE International Conference on Big Data (BigData 2018). [pdf] Acceptance rate: 19.7%
  14. S. Truex, L. Liu, M.E. Gursoy, and L. Yu. “Privacy-preserving inductive learning with decision trees”. 2017 IEEE International Congress on Big Data (BigData Congress 2017). [pdf]
  15. E. Esmerdag, M.E. Gursoy, A. Inan, and Y. Saygin. “Explode: An extensible platform for differentially private data analysis”. 16th IEEE International Conference on Data Mining (ICDM 2016). [pdf] Demo track
  16. A. Inan, M.E. Gursoy, E. Esmerdag, and Y. Saygin. “Graph-based modelling of query sets for differential privacy”. 28th International Conference on Scientific and Statistical Database Management (SSDBM 2016). [pdf]
  17. M.T. Garip, M.E. Gursoy, P. Reiher, and M. Gerla. “Congestion attacks to autonomous cars using vehicular botnets”. NDSS Workshop on Security of Emerging Networking Technologies (SENT 2015). [pdf]
  18. M.T. Garip, M.E. Gursoy, P. Reiher, and M. Gerla. “Scalable reactive vehicle-to-vehicle congestion avoidance mechanism”. In Proceedings of the 12th Annual Consumer Communications and Networking Conference (CCNC 2015), presented in the International Workshop on Vehicular Networking and Intelligent Transportation Systems (VENITS 2015). [pdf]

Patents

  1. V. Krishnamurthy and M.E. Gursoy. “Driver scoring and safe driving notifications”. US Patent 10,556,596 (granted).

Ph.D. Dissertation

  1. M.E. Gursoy. “Privacy-preserving data collection and sharing in modern mobile internet systems”. Ph.D. Dissertation, Georgia Institute of Technology. [pdf]