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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/117920...
Part of book or chapter of book . 2006 . Peer-reviewed
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DBLP
Conference object . 2017
Data sources: DBLP
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Hidden Pairings and Trapdoor DDH Groups

Authors: Alexander W. Dent; Steven D. Galbraith;

Hidden Pairings and Trapdoor DDH Groups

Abstract

This paper suggests a new building block for cryptographic protocols and gives two instantiations of it. The concept is to generate two descriptions of the same group: a public description that allows a user to perform group operations, and a private description that allows a user to also compute a bilinear pairing on the group. A user who has the private information can therefore solve decisional Diffie-Hellman (DDH) problems, and potentially also discrete logarithm problems. Some cryptographic applications of this idea are given. Both instantiations are based on elliptic curves. The first relies on the factoring assumption for hiding the pairing. The second relies on the difficulty of solving a system of multivariate equations. The second method also potentially gives rise to a practical trapdoor discrete logarithm system.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Top 10%
Average
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