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

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Mornewegstraße 32
64293 Darmstadt

+49 6151 16-27301

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

Publications

Ad-hoc secure two-party computation on mobile devices using hardware tokens

Author Daniel Demmler, Thomas Schneider, Michael Zohner
Date August 2014
Kind Inproceedings
Book title23rd USENIX Security Symposium (USENIX Security'14)
KeyTUD-CS-2014-0096
Research Areas CASED, Engineering Cryptographic Protocols, Secure Data, Secure Protocols, CYSEC
Abstract Secure two-party computation allows two mutually distrusting parties to jointly compute an arbitrary function on their private inputs without revealing anything but the result. An interesting target for deploying secure computation protocols are mobile devices as they contain a lot of sensitive user data. However, their resource restrictions make this a challenging task. In this work, we optimize and implement the secure computation protocol by Goldreich-Micali-Wigderson (GMW) on mobile phones. To increase performance, we extend the protocol by a trusted hardware token (i.e., a smartcard). The trusted hardware token allows to pre-compute most of the workload in an initialization phase, which is executed locally on one device and can be pre-computed independently of the later communication partner. We develop and analyze a proof-of-concept implementation of generic secure two-party computation on Android smart phones making use of a microSD smartcard. Our use cases include private set intersection for finding shared contacts and private scheduling of a meeting with location preferences. For private set intersection, our token-aided implementation on mobile phones is up to two orders of magnitude faster than previous generic secure two-party computation protocols on mobile phones and even as fast as previous work on desktop computers.
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