Javascript must be enabled to continue!
Montgomery Reduction for Gaussian Integers
View through CrossRef
Modular arithmetic over integers is required for many cryptography systems. Montgomery reduction is an efficient algorithm for the modulo reduction after a multiplication. Typically, Montgomery reduction is used for rings of ordinary integers. In contrast, we investigate the modular reduction over rings of Gaussian integers. Gaussian integers are complex numbers where the real and imaginary parts are integers. Rings over Gaussian integers are isomorphic to ordinary integer rings. In this work, we show that Montgomery reduction can be applied to Gaussian integer rings. Two algorithms for the precision reduction are presented. We demonstrate that the proposed Montgomery reduction enables an efficient Gaussian integer arithmetic that is suitable for elliptic curve cryptography. In particular, we consider the elliptic curve point multiplication according to the randomized initial point method which is protected against side-channel attacks. The implementation of this protected point multiplication is significantly faster than comparable algorithms over ordinary prime fields.
Title: Montgomery Reduction for Gaussian Integers
Description:
Modular arithmetic over integers is required for many cryptography systems.
Montgomery reduction is an efficient algorithm for the modulo reduction after a multiplication.
Typically, Montgomery reduction is used for rings of ordinary integers.
In contrast, we investigate the modular reduction over rings of Gaussian integers.
Gaussian integers are complex numbers where the real and imaginary parts are integers.
Rings over Gaussian integers are isomorphic to ordinary integer rings.
In this work, we show that Montgomery reduction can be applied to Gaussian integer rings.
Two algorithms for the precision reduction are presented.
We demonstrate that the proposed Montgomery reduction enables an efficient Gaussian integer arithmetic that is suitable for elliptic curve cryptography.
In particular, we consider the elliptic curve point multiplication according to the randomized initial point method which is protected against side-channel attacks.
The implementation of this protected point multiplication is significantly faster than comparable algorithms over ordinary prime fields.
Related Results
Encoder Hurwitz Integers: Hurwitz Integers that have the “Division with Small Remainder” Property
Encoder Hurwitz Integers: Hurwitz Integers that have the “Division with Small Remainder” Property
Considering error-correcting codes over Hurwitz integers, prime Hurwitz integers are considered. On the other hand, considering transmission over Gaussian channel, Hurwitz integers...
Encoder Hurwitz Integers: The Hurwitz integers that have the ”division with small division” property
Encoder Hurwitz Integers: The Hurwitz integers that have the ”division with small division” property
Abstract
The residue class set of a Hurwitz integer is constructed by modulo function with primitive Hurwitz integer whose norm is a prime integer, i.e. prime Hurwitz integ...
Odd version Mathieu-Gaussian beam based on Green function
Odd version Mathieu-Gaussian beam based on Green function
Like the theoretical pattern of non-diffracting Bessel beams, ideal non-diffracting Mathieu beams also carry infinite energy, but cannot be generated as a physically realizable ent...
A Compact Coprocessor for the Elliptic Curve Point Multiplication over Gaussian Integers
A Compact Coprocessor for the Elliptic Curve Point Multiplication over Gaussian Integers
This work presents a new concept to implement the elliptic curve point multiplication (PM). This computation is based on a new modular arithmetic over Gaussian integer fields. Gaus...
Rosa Parks
Rosa Parks
On December 1, 1955, Rosa Parks refused to give up her seat on a Montgomery bus and was arrested. Her courageous action galvanized a yearlong community boycott and helped usher in ...
Data-driven Warping of Gaussian Processes for Spatial Interpolation of Skewed Data
Data-driven Warping of Gaussian Processes for Spatial Interpolation of Skewed Data
<p>Gaussian processes are a flexible machine learning framework that can be used for spatial interpolation and space-time prediction as well. Gaussian process regress...
Adaptive and augmented nonlinear filters : theory and applications
Adaptive and augmented nonlinear filters : theory and applications
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Nonlinear estimation and filtering have been intensively studied for decades since it has been widely used in...
Montgomery's legal and practical impact: A systematic review at 6 years
Montgomery's legal and practical impact: A systematic review at 6 years
AbstractRationale, Aims and ObjectivesSix years ago, the Supreme Court judgement in Montgomery v Lanarkshire changed medical law. It introduced a new patient‐based standard of care...

