Daniel Demmler, M.Sc.

I am a Ph.D. student and member of the Engineering Cryptographic Protocols (ENCRYPTO) group at the Center for Research in Security and Privacy (CRISP).

My research focuses on the design, implementation and evaluation of secure multi-party computation and private information retrieval protocols, as well as privacy-preserving applications and their practical realization.

In case you want to contact me securely, send me an encrypted e-mail using my undefinedPGP public key. Its fingerprint: 91DC D028 AA37 E1F9 4D06 1BD3 8740 013C 6881 7144.

Contact

S4|14 5.3.10
Mornewegstraße 32
64293 Darmstadt

+49 6151 16-27301

daniel.demmler(a-t)crisp-da.de

Publications

Automated Synthesis of Optimized Circuits for Secure Computation

Author Daniel Demmler, Ghada Dessouky, Farinaz Koushanfar, Ahmad-Reza Sadeghi, Thomas Schneider, Shaza Zeitouni
Date October 2015
Kind Inproceedings
Book title22nd ACM Conference on Computer and Communications Security (CCS'15)
LocationDenver, Colorado, USA
KeyTUD-CS-2015-1340
Research Areas System Security Lab, E4, CYSEC, Engineering Cryptographic Protocols, Solutions, S2, Primitives, P3, CROSSING, Engineering
Abstract In the recent years, secure computation has been the subject of intensive research, emerging from theory to practice. In order to make secure computation usable by non-experts, Fairplay (USENIX Security 2004) initiated a line of research in compilers that allow to automatically generate circuits from high-level descriptions of the functionality that is to be computed securely. Most recently, TinyGarble (IEEE S\&P 2015) demonstrated that it is natural to use existing hardware synthesis tools for this task. In this work, we present how to use industrial-grade hardware synthesis tools to generate circuits that are not only optimized for size, but also for depth. These are required for secure computation protocols with non-constant round complexity. We compare a large variety of circuits generated by our toolchain with hand-optimized circuits and show reduction of depth by up to 14\%. The main advantages of our approach are developing customized libraries of depth-optimized circuit constructions which we map to high-level functions and operators, and using existing libraries available in the industrial-grade logic synthesis tools which are heavily tested. In particular, we show how to easily obtain circuits for IEEE 754 compliant floating-point operations. We extend the open source ABY framework (NDSS 2015) to securely evaluate circuits generated with our toolchain and show between 0.5 to 21.4 times faster floating-point operations than previous protocols of Aliasgari et al. (NDSS 2013), even though our protocols work for two parties instead of three or more. As application we consider privacy-preserving proximity testing on Earth.
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