2005
DOI: 10.1007/11545262_7
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Short Memory Scalar Multiplication on Koblitz Curves

Abstract: Abstract. We present a new method for computing the scalar multiplication on Koblitz curves. Our method is as fast as the fastest known technique but requires much less memory. We propose two settings for our method. In the first setting, well-suited for hardware implementations, memory requirements are reduced by 85%. In the second setting, well-suited for software implementations, our technique reduces the memory consumption by 70%. Thus, with much smaller memory usage, the proposed method yields the same ef… Show more

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Cited by 9 publications
(9 citation statements)
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“…This is not a problem if a normal basis is used to represent the field, but may induce a performance penalty with a polynomial basis. A similar problem was faced by the authors of [20], and they solved it adapting an idea from [21]. The idea consists in keeping a copy R of the point P in normal basis representation.…”
Section: Return (X)mentioning
confidence: 99%
See 1 more Smart Citation
“…This is not a problem if a normal basis is used to represent the field, but may induce a performance penalty with a polynomial basis. A similar problem was faced by the authors of [20], and they solved it adapting an idea from [21]. The idea consists in keeping a copy R of the point P in normal basis representation.…”
Section: Return (X)mentioning
confidence: 99%
“…Usual windowed methods with precomputations have, of course, similar time complexity but use storage for 2 w−2 −1 points [23,24] and thus O(n2 w ) = O(n 2 / log n) bits of memory. Algorithms 3 and 4 need O(n 2 ) bits of field-dependent (but not point-dependent) data for base conversion (as in [21,20]) that can be stored statically (such as in ROM).…”
Section: A Performance Remarkmentioning
confidence: 99%
“…The relations between the f j 's and their inverses must then be given explicitly. In [19] this is done for w = 5. Even though the authors cannot present the results in a completely general way, in the case described in [19] the reduction in memory consumption (or, equivalently, the speed-up with respect to other methods with no precomputations) is noteworthy.…”
Section: Further Developments In τ -Adic Representationsmentioning
confidence: 99%
“…One solution is provided, as already mentioned, by a technique introduced by Park et al in [20] and used by Okeya et al in [19]. Instead of applying a variable power of the Frobenius to a changing point as done in Steps 5 to 9 if Algorithm 3, we apply the Frobenius to the point P and accumulate directly.…”
Section: On the Use Of Normal Vs Polynomial Basesmentioning
confidence: 99%
“…This is not a problem if a normal basis is used to represent the field, but may induce a performance penalty with a polynomial basis. A similar problem was faced by Okeya, Takagi and Vuillaume in [16], and they solved it adapting an idea by Park, Sim and Lee [17]. The technique consists in keeping a copy R of the point P in normal basis representation.…”
Section: Return (X)mentioning
confidence: 98%