Recent publications
Article
Salem, A, Berrang, P, Humbert, M & Backes, M 2019, 'Privacy-Preserving Similar Patient Queries for Combined Biomedical Data', PoPETs, vol. 2019, no. 1, pp. 47-67. https://doi.org/10.2478/popets-2019-0004
Conference article
Wu, Y, He, X, Berrang, P, Humbert, M, Backes, M, Gong, N & Zhang, Y 2024, 'Link Stealing Attacks Against Inductive Graph Neural Networks', PoPETs, vol. 2024, no. 4, pp. 818–839. https://doi.org/10.56553/popets-2024-0143
Berrang, P, Gerhart, P & Schröder, D 2024, 'Measuring Conditional Anonymity—A Global Study', PoPETs, vol. 2024, no. 4, pp. 947–966. https://doi.org/10.56553/popets-2024-0150
Raab, R, Berrang, P, Gerhart, P & Schröder, D 2024, 'SoK: Descriptive Statistics Under Local Differential Privacy', PoPETs.
Conference contribution
Wu, Y, Wen, R, Backes, M, Berrang, P, Humbert, M, Shen, Y & Zhang, Y 2024, Quantifying Privacy Risks of Prompts in Visual Prompt Learning. in Proceedings of the 33rd USENIX Security Symposium. USENIX , pp. 5841-5858. <https://www.usenix.org/conference/usenixsecurity24/presentation/wu-yixin>
Esiyok, I, Berrang, P, Cohn-Gordon, K & Kuennemann, R 2023, Accountable Javascript Code Delivery. in NDSS Symposium 2023 Accepted Papers., f96, The Internet Society, pp. 1-17, Network and Distributed System Security (NDSS) Symposium 2023, San Diego, California, United States, 27/02/23. https://doi.org/10.14722/ndss.2023.24096
Yang, Z, He, X, Li, Z, Backes, M, Humbert, M, Berrang, P & Zhang, Y 2023, Data Poisoning Attacks Against Multimodal Encoders. in A Krause, E Brunskill, K Cho, B Engelhardt, S Sabato & J Scarlett (eds), Proceedings of the 40th International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 202, Proceedings of Machine Learning Research, pp. 39299-39313, The Fortieth International Conference on Machine Learning, Honolulu, Hawaii, United States, 23/07/23. <https://proceedings.mlr.press/v202/yang23f/yang23f.pdf>
Wang, Z, Chaliasos, S, Qin, K, Zhou, L, Gao, L, Berrang, P, Livshits, B & Gervais, A 2023, On how zero-knowledge proof blockchain mixers improve, and worsen user privacy. in WWW '23: Proceedings of the ACM Web Conference 2023. Association for Computing Machinery (ACM), pp. 2022-2032, The Web Conference 2023, Austin, Texas, United States, 30/04/23. https://doi.org/10.1145/3543507.3583217
Backes, M, Berrang, P, Hanzlik, L & Pryvalov, I 2022, A framework for constructing Single Secret Leader Election from MPC. in V Atluri, R Di Pietro, CD Jensen & W Meng (eds), Computer Security – ESORICS 2023: 27th European Symposium on Research in Computer Security, Copenhagen, Denmark, September 26–30, 2022, Proceedings, Part II. 1 edn, Lecture Notes in Computer Science, vol. 13555, Springer, Cham, pp. 672–691, 27th European Symposium on Research in Computer Security, Copenhagen, Denmark, 26/09/22. https://doi.org/10.1007/978-3-031-17146-8_33
Hagestedt, I, Humbert, M, Berrang, P, Lehmann, I, Eils, R, Backes, M & Zhang, Y 2020, Membership Inference Against DNA Methylation Databases. in IEEE European Symposium on Security and Privacy (EuroS&P).
Hagestedt, I, Zhang, Y, Humbert, M, Berrang, P, Tang, H, Wang, X & Backes, M 2019, MBeacon: Privacy-Preserving Beacons for DNA Methylation Data. in Proceedings of the 26th Annual Network and Distributed System Security Symposium (NDSS).
Salem, A, Zhang, Y, Humbert, M, Berrang, P, Fritz, M & Backes, M 2019, ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models. in Proceedings of the 26th Annual Network and Distributed System Security Symposium (NDSS).
Berrang, P, Humbert, M, Zhang, Y, Lehmann, I, Eils, R & Backes, M 2018, Dissecting Privacy Risks in Biomedical Data. in Proceedings of the 2018 IEEE European Symposium on Security and Privacy (EuroSP). IEEE.
Backes, M, Berrang, P, Bieg, M, Eils, R, Herrmann, C, Humbert, M & Lehmann, I 2017, Identifying Personal DNA Methylation Profiles by Genotype Inference. in Proceedings of the 38th IEEE Symposium on Security and Privacy (S&P). IEEE, pp. 957-976.
Doctoral Thesis
Berrang, P 2017, 'Quantifying and Mitigating Privacy Risks in Biomedical Data', Saarland University. https://doi.org/doi:10.22028/D291-27302
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