2010
DOI: 10.1007/978-3-642-12133-3_9
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Parametric Encryption Hardware Design

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Cited by 10 publications
(10 citation statements)
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“…6, for the Montgomery multiplier, high frequency errors are localized to a few (r, p) tuples. 2 This is not the case for the exponentiation module whose average frequency error is high and close to the maximum frequency error. Here, the reference point chosen to determine f 0 ((r, p) = (1, 1)) has a maximum frequency, which is around 15% lower than for the other values of p, leading to a constant error.…”
Section: A Accuracy Of the Modelmentioning
confidence: 98%
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“…6, for the Montgomery multiplier, high frequency errors are localized to a few (r, p) tuples. 2 This is not the case for the exponentiation module whose average frequency error is high and close to the maximum frequency error. Here, the reference point chosen to determine f 0 ((r, p) = (1, 1)) has a maximum frequency, which is around 15% lower than for the other values of p, leading to a constant error.…”
Section: A Accuracy Of the Modelmentioning
confidence: 98%
“…Common applications falling into this category are bitwise algorithms for which the result is updated at each iteration based on the corresponding bit of one or several inputs. In cryptography, this is for instance the case of the Montgomery multiplication algorithm [14], the square-multiply exponentiation algorithm [2], and the Lucas primality test [15], [16]. Some important arithmetic algorithms, such as the integer square root [17] and the restoring division algorithms also follow this pattern.…”
Section: A Main Ideamentioning
confidence: 99%
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“…The modular exponentiation module is based on the Montgomery multiplier presented in [18]. The square and multiply operations are both performed by the Montgomery multiplier, which makes them hardly distinguishable.…”
Section: B Study Case: Modular Exponentiationmentioning
confidence: 99%