Humboldt-Universität zu Berlin - Mathematisch-Naturwissenschaftliche Fakultät - Institut für Informatik

- Info
Humboldt-Universität zu Berlin
|
Mathematisch-Naturwissenschaftliche Fakultät
|
Institut für Informatik
|
Benutzer
|
Phillipp Schoppmann
Phillipp Schoppmann

Ich arbeite als Research Scientist bei Google und bin Doktorand am Lehrstuhl für Technische Informatik an der Humboldt-Universität zu Berlin. Zuvor habe ich einen Master of Science an der University of Edinburgh in Schottland abgeschlossen.
Forschung
Meine Schwerpunkte liegen in den Bereichen
- IT- und Netzwerksicherheit
- Datenschutz und Datensicherheit
- Kryptographie
- Verteilte Systeme
- Secure Multiparty Computation
Kontakt
schoppmann@informatik.hu-berlin.de
+49 30 2093 3039
D172 1A11 E09B 4281 B155 F672 2250 016F 53AC 6F7E
Postadresse
Humboldt-Universität zu Berlin
Institut für Informatik
Unter den Linden 6
10099 Berlin
Besucheradresse
Johann-von-Neumann-Haus
Haus IV, Raum 304
Rudower Chaussee 25
12489 Berlin
Publikationen
Journal Articles
S. Stammler,
T. Kussel,
P. Schoppmann,
F. Stampe,
G. Tremper,
S. Katzenbeisser,
K. Hamacher, and
M. Lablans
Mainzelliste SecureEpiLinker (MainSEL): Privacy-Preserving Record Linkage using Secure Multi-Party Computation
Bioinformatics, 2020
URL, DOI, BibTex
Mainzelliste SecureEpiLinker (MainSEL): Privacy-Preserving Record Linkage using Secure Multi-Party Computation
Bioinformatics, 2020
URL, DOI, BibTex
P. Schoppmann,
L. Vogelsang,
A. Gascón, and
B. Balle
Secure and Scalable Document Similarity on Distributed Databases: Differential Privacy to the Rescue
Proceedings on Privacy Enhancing Technologies (PETS '20), 2020
URL, DOI, BibTex
Secure and Scalable Document Similarity on Distributed Databases: Differential Privacy to the Rescue
Proceedings on Privacy Enhancing Technologies (PETS '20), 2020
URL, DOI, BibTex
A. Gascón,
P. Schoppmann,
B. Balle,
M. Raykova,
J. Doerner,
S. Zahur, and
D. Evans
Privacy Preserving Distributed Linear Regression on High-Dimensional Data
Proceedings on Privacy Enhancing Technologies (PETS '17), 2017
URL, DOI, BibTex
Privacy Preserving Distributed Linear Regression on High-Dimensional Data
Proceedings on Privacy Enhancing Technologies (PETS '17), 2017
URL, DOI, BibTex
Conference Papers
P. Rindal and
P. Schoppmann
VOLE-PSI: Fast OPRF and Circuit-PSI from Vector-OLE
Annual International Conference on the Theory and Applications of Cryptographic Techniques (EUROCRYPT '21), 2021
URL, BibTex
VOLE-PSI: Fast OPRF and Circuit-PSI from Vector-OLE
Annual International Conference on the Theory and Applications of Cryptographic Techniques (EUROCRYPT '21), 2021
URL, BibTex
L. Vogelsang,
M. Lehne,
P. Schoppmann,
F. Prasser,
S. Thun,
B. Scheuermann, and
J. Schepers
A Secure Multi-Party Computation Protocol for Time-To-Event Analyses
Proceedings of MIE 2020: Digital Personalized Health and Medicine, IOS Press, 2020
DOI, PDF, BibTex
A Secure Multi-Party Computation Protocol for Time-To-Event Analyses
Proceedings of MIE 2020: Digital Personalized Health and Medicine, IOS Press, 2020
DOI, PDF, BibTex
P. Schoppmann,
A. Gascón,
L. Reichert, and
M. Raykova
Distributed Vector-OLE: Improved Constructions and Implementation
ACM Conference on Computer and Communications Security (CCS '19), ACM, 2019
URL, DOI, BibTex
Distributed Vector-OLE: Improved Constructions and Implementation
ACM Conference on Computer and Communications Security (CCS '19), ACM, 2019
URL, DOI, BibTex
P. Schoppmann,
A. Gascón,
M. Raykova, and
B. Pinkas
Make Some ROOM for the Zeros: Data Sparsity in Secure Distributed Machine Learning
ACM Conference on Computer and Communications Security (CCS '19), ACM, 2019
URL, DOI, BibTex
Make Some ROOM for the Zeros: Data Sparsity in Secure Distributed Machine Learning
ACM Conference on Computer and Communications Security (CCS '19), ACM, 2019
URL, DOI, BibTex
Technical Reports
A. Ali,
T. Lepoint,
S. Patel,
M. Raykova,
P. Schoppmann,
K. Seth, and
K. Yeo
Communication–Computation Trade-offs in PIR
IACR Cryptology ePrint Archive, 2019
URL, BibTex
Communication–Computation Trade-offs in PIR
IACR Cryptology ePrint Archive, 2019
URL, BibTex
Workshop Presentations
N. Angelou,
A. Benaissa,
B. Cebere,
W. Clark,
A. J. Hall,
M. A. Hoeh,
D. Liu,
P. Papadopoulos,
et al.
Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning
NeurIPS 2020 Workshop on Privacy Preserving Machine Learning (PPML '20), 2020
URL, BibTex
Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning
NeurIPS 2020 Workshop on Privacy Preserving Machine Learning (PPML '20), 2020
URL, BibTex