Sebastian Meiser

Staff Research Scientist

Research Areas: Quantifiable Privacy Guarantees, Anonymous Communication, and Information Security

Sebastian Meiser, Visa Research scientist.

Biography

Dr. Sebastian Meiser joined Visa Research as a Staff Research Scientist in June 2019. Sebastian received his Ph.D. from Saarland University in Germany in 2016, where he graduated summa cum laude. His thesis focused on quantifiable anonymity guarantees for the Tor network. After his Ph.D., Sebastian was a postdoctoral research associate and lecturer at University College London in the U.K. until 2019, before joining Visa Research soon thereafter. 

As a member of the Security team, his research interests are in information security—in particular, quantifiable privacy guarantees, privacy preserving machine learning, anonymous communication, and cryptography. He has published multiple papers in several international conferences, including IEEE Symposium on Security and Privacy (S&P), Association for Computing Machinery Conference on Computer and Communications Security (CCS), Privacy Enhancing Technologies Symposium (PETS), International Conference on Applied Cryptography and Network Security (ACNS) and others. 

Conferences

  • Sommer, D. M., Meiser, S., & Mohammadi, E. (2019). Privacy Loss Classes: The Central Limit Theorem in Differential Privacy. Proceedings on Privacy Enhancing Technologies, 2019(2), 245–269. 
  • Meiser, S, & Mohammadi, E. (2018). Tight on Budget? Tight Bounds for r-Fold Approximate Differential Privacy. 25th ACM Conference on Computer and Communications Security, 2018.
  • Das, D., Meiser, S., Mohammadi, E., & Kate, A. (2018). Anonymity Trilemma: Strong Anonymity, Low Bandwidth Overhead, Low Latency - Choose Two. 2018 IEEE Symposium on Security and Privacy (SP).
  • Piotrowska, A., Hayes, J., Elahi, T., Leuven, K., Meiser, S., & Danezis, G. (2017). The Loopix Anonymity System. 26th Usenix Security Symposium, 2017.
  • Backes, M., Meiser, S., & Schröder, D. (2016). Delegatable Functional Signatures. Public Key Cryptography – PKC, 2016, 357-386.
  • Backes, M., Meiser, S., Slowik, M. (2016). Your Choice MATor(s): Large-scale Quantitative Anonymity Assessment of Tor Path Selection Algorithms Against Structural Attacks. Proceedings on Privacy Enhancing Technologies, 2016(2), 40–60.
  • Backes, M., Kate, A., Meiser, S., & Ruffing, T. (2015). Secrecy Without Perfect Randomness: Cryptography with (Bounded) Weak Sources. Applied Cryptography and Network Security, 675–695.
  • Backes, M., Kate, A., Meiser, S., & Mohammadi, E. (2014). Nothing else MATor(s): Monitoring the Anonymity of Tor’s Path Selection. ACM SIGSAC Conference on Computer and Communications Security, 2014.
  • Backes, M., Kate, A., Manoharan, P., Meiser, S., & Mohammadi, E. (2013). AnoA: A Framework for Analyzing Anonymous Communication Protocols. 2013 IEEE Computer Security Foundations Symposium.