Personal profile
Biography
Marc Juarez is a Lecturer in Cyber Security and Privacy at the University of Edinburgh’s School of Informatics. Before joining the University of Edinburgh, Marc was a Postdoctoral Scholar in the Computer Science Department of the University of Southern California. Marc obtained his PhD from the KU Leuven, under an FWO PhD fellowship. At the KU Leuven, he worked in the Computer Security and Industrial Cryptography (COSIC) group. His thesis was a runner-up for the 2020 ACM SIGSAC Doctoral Dissertation Award.
Research Interests
- ML-Based Traffic Analysis: the development and evaluation of defenses from both a practical and theoretical point of view.
- Security and Privacy of ML: the design of methods to audit privacy and security of ML models; the development of privacy-aware ML.
- Privacy and Fairness: the study of disparate privacy risks across demographics; the privacy challenges that arise from identifying and mitigating algorithmic bias.
Qualifications
- PhD in Engineering Science: Electrical Engineering, 2019. KU Leuven
- Double degree in Mathematics (BA) and Computer Engineering (BA + MSc), 2013. Universitat Autònoma de Barcelona
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Collaborations and top research areas from the last five years
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Black-box evasion attacks on data-driven Open RAN apps: Tailored design and experimental evaluation
Gajjar, P., Khoja, M., Ganiyu, A., Juarez, M., Marina, M. K., Lehane, A. & Shah, V. K., 25 Nov 2025, Proceedings of the ACM on Networking. CoNEXT4 ed. Association for Computing Machinery (ACM), Vol. 3. p. 1-26 53. (Proceedings of the ACM on Networking).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile -
Rethinking the Role of Network Stacks for Website Fingerprinting Defense
Lavrentieva, L., Juarez, M. & Honda, M., 17 Nov 2025, Rethinking the Role of Network Stacks for Website Fingerprinting Defense. Workshop on Hot Topics in Networks: Association for Computing Machinery (ACM), p. 254-262 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile -
Shift your shape: Correlating and defending mixnet flows based on their shapes
Oldenburg, L., Juarez, M., Argones Rúa, E. & Diaz, C., 6 Oct 2025, In: IEEE Transactions on Dependable and Secure Computing. 23, 1, p. 1466-1483 18 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile -
A crack in the bark: Leveraging public knowledge to remove Tree-Ring watermarks
Lin, J. & Juarez, M., 13 Aug 2025, Proceedings of the 34th USENIX Security Symposium. USENIX Association, p. 7331-7348 18 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile -
SoK: What makes private learning unfair?
Yao, K. & Juarez, M., 13 Dec 2024, (Accepted/In press) Proceedings of the 3rd IEEE Conference on Secure and Trustworthy Machine Learning. Institute of Electrical and Electronics Engineers, p. 1-17 17 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile
Datasets
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A Crack in the Bark: Leveraging Public Knowledge to Remove Tree-Ring Watermarks
Lin, J. (Creator) & Juarez, M. (Creator), Zenodo, 4 Jun 2025
DOI: 10.5281/zenodo.15595720, https://zenodo.org/records/15595720
Dataset
Press/Media
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Deepfakes can bypass detection tools using simple image edits, study finds
25/03/26
1 Media contribution
Press/Media: Research
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“AI Fingerprints” Easily Removed or Forged, Finds Edinburgh Study
25/03/26
1 Media contribution
Press/Media: Research