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SIMAP - Secure Information Management and Processing

Case

SIMAP - Secure Information Management and Processing

Secure benchmarking and auction solutions

State-of-the-art cryptography enables secure processing of personal data.

In many situations it is highly valuable to keep private information secret, and confidentiality and security is therefore a top priority. On the other hand the combination of private information from different sources can be just as valuable. How can this combination be realised without compromising individual privacy? 

SIMAP – Secure Information Management and Processing – provided general and specific solutions to the fundamental problem of sharing secret knowledge without compromising the secrets.  

The project covered basic research and running prototypes and set new standards for how securely and efficiently secret information can be shared.

SIMAP provided general and specific solutions to the fundamental problem of sharing secret knowledge without compromising the secrets. This was done in a collaboration involving three fields of research: 

  1. Cryptology, which provides the technical foundation,
  2. Information economics, which provides a theoretical description of the applications, 
  3. Programming languages, which tie together cryptology and information economics, thus making it easier to apply cryptographic primitives to realise the desired use in running software – in a secure manner.

The project ranged from basic research to running prototypes and set new standards for how securely and efficiently secret knowledge can be shared.

The primary research result of the project is the world’s first practical application of Secure Multiparty Computation.

This is described in this article:

Multiparty Computation Goes Live. Thirteenth International Conference on Financial Crypto and Data Security ‘09 (FC’09). Barbados, 2009, Peter Bogetoft, Dan Lund Christensen, Ivan Damgård, Martin Geisler, Thomas Jakobsen, Mikkel Krøigaard, Janus Dam Nielsen, Jesper Buus Nielsen, Kurt Nielsen, Jakob Illeborg Pagter, Michael Schwartzbach, and Tomas Toft.

The applications are wide-ranging and have the potential to include all situations where secret information is involved.

Examples include correlation of personal information from different sources (databases), benchmarking of industries for learning or motivational purposes, or auctions where the coordination of private information contributes to fixing the right allocation and price of the commodities for sale.

The project has led to the establishment of a spin-off company, Partisia Market Design, co-owned by the Alexandra Institute.

Copenhagen Business School

Danisco

Copenhagen University

Aarhus University - Department of Computer Science

 

The project was funded by The Strategic Research Council – Growth Technologies.

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