Projects per year
Personal profile
Biography
Natasha is a lecturer in Cybersecurity with special interests in privacy-preserving technologies and mathematical techniques for analysing information leaks in secure systems. She holds an undergraduate degree in Pure Mathematics and Computer Science from the University of Sydney, and a PhD in Computing from Macquarie University and École Polytechnique in France. Natasha has also worked extensively in industry as a software engineer specialising in backend web applications.
Natasha's research interests are in the mathematical foundations of data privacy, particularly involving differential privacy, natural language processing or machine learning. Her work involves probabilistic reasoning using quantitative information flow techniques which derive from information-theoretic principles.
Natasha's research aims at developing mathematical principles to support the analysis of privacy-preserving systems, as well as the development of software tools to support the application of these mathematical techniques in practical engineering scenarios.
Research interests
data privacy, differential privacy, privacy-preserving natural language processing, privacy-preserving machine learning, information flow for privacy and security
Education/Academic qualification
Computing, PhD, Differential Privacy for Metric Spaces: Information-Theoretic Models for Privacy and Utility with New Applications to Metric Domains, Macquarie University
Award Date: 19 Aug 2021
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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DP25: Consumer Data Privacy Risk Analysis and Management in the Open Banking Era
Smith, T. (Primary Chief Investigator), Liao, Y. (Chief Investigator), Bu, D. (Chief Investigator), Fernandes, N. (Chief Investigator), Selvadurai, N. (Chief Investigator) & Alvim, M. S. (Partner Investigator)
13/03/25 → 12/03/28
Project: Research
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Generalisable Models for Heterogenous Devices Traffic Inference
Gharakheili, H. (Chief Investigator), Batista, G. E. (Chief Investigator), Rui, S. (Chief Investigator), Mishra, D. (Chief Investigator), Sheng, M. (Primary Chief Investigator), Fernandes, N. (Chief Investigator) & Bennett, A. (Partner Investigator)
1/03/24 → 1/09/25
Project: Research
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MQ FCRC: Privacy Analyses for Financial Transaction Data Communications Protocol
Fernandes, N. (Primary Chief Investigator), Liao, Y. (Primary Chief Investigator) & Bu, D. (Primary Chief Investigator)
31/08/23 → 31/08/24
Project: Research
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PRSW23: Google ExploreCSR Grant- Undergraduate Research Skills- 2023
Roberts, M. (Primary Chief Investigator), Ramakrishnan, C. (Chief Investigator) & Fernandes, N. (Chief Investigator)
21/09/22 → 30/06/23
Project: Research
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UAV_TF: Google ExploreCSR Grant-Tensor Flow for UAV-2022
Roberts, M. (Primary Chief Investigator), Ramakrishnan, C. (Associate Investigator), Fernandes, N. (Associate Investigator) & Pappas, C. (Associate Investigator)
30/11/21 → 30/11/22
Project: Research
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Composition theorems for f-differential privacy
Fernandes, N., McIver, A. & Sadeghi, P., 2026, Foundations of Software Science and Computation Structures: 29th International Conference, FoSSaCS 2026, held as part of the International Joint Conferences on Theory and Practice of Software, ETAPS 2026, Turin, Italy, April 11-16, 2026, proceedings. Bertrand, N. & Milius, S. (eds.). Cham, Switzerland: Springer, Springer Nature, p. 462-483 22 p. (Lecture Notes in Computer Science; vol. 16503).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
Open AccessFile1 Downloads (Pure) -
Real-time and trustworthy classification of IoT traffic using lightweight deep learning
Sivanathan, A., Mishra, D., Ruj, S., Fernandes, N., Sheng, Q. Z., Tran, M., Luo, B., Coscia, D., Batista, G. & Habibi Gharakaheili, H., 2026, In: IEEE Transactions on Network Science and Engineering. 13, p. 3256-3273 18 p.Research output: Contribution to journal › Article › peer-review
2 Link opens in a new tab Citations (Scopus) -
Empirical calibration and metric differential privacy in language models
Faustini, P., Fernandes, N., McIver, A. & Dras, M., Nov 2025, In: IEEE Access. 13, p. 196024-196039 16 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile1 Link opens in a new tab Citation (Scopus)3 Downloads (Pure) -
Formal privacy analyses for Open Banking
Soares, L. D. C., Alvim, M. S., Bu, D., Fernandes, N. & Liao, Y., 2025, Formal Methods: foundations and applications : 27th Brazilian Symposium, SBMF 2024, Vitória, Brazil, December 4-6, 2024, proceedings. C. Nogueira, S. & Teodorov, C. (eds.). Cham: Springer, Springer Nature, p. 171-193 23 p. (Lecture Notes in Computer Science; vol. 15403).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
1 Link opens in a new tab Citation (Scopus) -
On the challenges of formal privacy models for open banking
Soares, L. D. C., Alvim, M. S., Bu, D., Fernandes, N. & Liao, Y., 2025, CADE 2025: Proceedings of the 11th International Conference on AI and the Digital Economy. Venice, Italy: The Institution of Engineering and Technology (IET), p. 104-108 5 p. (IET Conference Proceedings; vol. 2025, no. 42).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review