Thijs Veugen

- Full Name
- P.J.M. Veugen
- Function(s)
- Researcher - TNO
- P.J.M.Veugen@cwi.nl
- Telephone
- +31 20 592 4051
- Room
- M266
- Department(s)
- Cryptology
Biography
I'm a senior scientist at TNO, working on applied cryptography. You will find me in the Cryptology group of CWI each Friday. My goal is to show society the beauty of secure multi-party computation, and all the nice applications it has.
Publications
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Kamphorst, B, Rooijakkers, T, Veugen, P.J.M, Cellamare, M, & Knoors, D. (2022). Accurate training of the Cox proportional hazards model on vertically-partitioned data while preserving privacy. BMC Medical Informatics and Decision Making, 22(1), 49.1–49.18. doi:10.1186/s12911-022-01771-3
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Veugen, P.J.M. (2022). Lightweight secure integer comparison. Mathematics, 10(3), 305.1–305.18. doi:10.3390/math10030305
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van Egmond, M.B, Spini, G, van der Galiën, O, IJpma, A, Veugen, P.J.M, Kraaij, W, … Kooij-Janic, M. (2021). Privacy-preserving dataset combination and Lasso regression for healthcare predictions. BMC Medical Informatics and Decision Making, 21, 266‐1–266‐16. doi:10.1186/s12911-021-01582-y
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Veugen, P.J.M, Kamphorst, B, van de L’Isle, N, & van Egmond, M.B. (2021). Privacy-preserving coupling of vertically-partitioned databases and subsequent training with gradient descent. In Cyber Security Cryptography and Machine Learning (pp. 38–51). doi:10.1007/978-3-030-78086-9_3
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Veugen, P.J.M. (2020). Efficient coding for secure computing with additively-homomorphic encrypted data. International Journal of Applied Cryptography, 4(1), 1–15. doi:10.1504/IJACT.2020.107160
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Spini, G, van Heesch, M, Veugen, P.J.M, & Chatterjea, S. (2019). Private hospital workflow optimization via secure k-means clustering. Journal of Medical Systems, 44(1). doi:10.1007/s10916-019-1473-4
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Sangers, A, van Heesch, M, Attema, T, Veugen, P.J.M, Wiggerman, M, Veldsink, J, … Worm, D.T.H. (2019). Secure multiparty PageRank algorithm for collaborative fraud detection. In Proceedings of International Conference on Financial Cryptography and Data Security (pp. 605–623). doi:10.1007/978-3-030-32101-7_35
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de Ridder, F, Neumann, N.M.P, Veugen, P.J.M, & Kooij, R.E. (2019). A quantum algorithm for minimising the effective graph resistance upon edge addition. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 63–73). doi:10.1007/978-3-030-14082-3_6
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Nateghizad, M, Veugen, P.J.M, Erkin, Z, & Lagendijk, R.L. (2018). Secure equality testing protocols in the two-party setting. In ARES 2018: International Conference on Availability, Reliability and Security. doi:10.1145/3230833.3230866
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Veeningen, M, Chatterjea, S, Horváth, A.Z, Spindler, G, Boersma, E, van der Spek, P, … Veugen, P.J.M. (2018). Enabling analytics on sensitive medical data with secure multi-party computation. In Studies in Health Technology and Informatics (pp. 76–80). doi:10.3233/978-1-61499-852-5-76