Galbraith, Lin, and Scott recently constructed efficiently computable endomorphisms for a large family of elliptic curves defined over IFq2 and showed, in the case where q is a prime, that the Gallant-Lambert-Vanstone point multiplication method for these curves is significantly faster than point multiplication for general elliptic curves over prime fields. In this paper, we investigate the potential benefits of using Galbraith-Lin-Scott elliptic curves in the case where q is a power of 2. The analysis differs from the q prime case because of several factors, including the availability of the point halving strategy for elliptic curves over binary fields. Our analysis and implementations show that Galbraith-Lin-Scott point multiplication method offers significant acceleration for curves over binary fields, in both doubling- and halving-based approaches. Experimentally, the acceleration surpasses that reported for prime fields (for the platform in common), a somewhat counterintuitive result given the relative costs of point addition and doubling in each case.

Fast algorithms for multiplication in finite fields are required for several cryptographic applications, in particular for implementing elliptic curve operations over binary fields F/sub 2m/. In this paper, we present new software algorithms for efficient multiplication over F/sub 2m/ that use a Gaussian normal basis representation. Two approaches are presented, direct normal basis multiplication and a method that exploits a mapping to a ring where fast polynomial-based techniques can be employed. Our analysis, including experimental results on an Intel Pentium family processor, shows that the new algorithms are faster and can use memory more efficiently than previous methods. Despite significant improvements, we conclude that the penalty in multiplication is still sufficiently large to discourage the use of normal bases in software implementations of elliptic curve systems.

We present a careful analysis of elliptic curve point multiplication methods that use the point halving technique of Knudsen and Schroeppel and compare these methods to traditional algorithms that use point doubling. The performance advantage of halving methods is clearest in the case of point multiplication kP, where P is not known in advance and smaller field inversion to multiplication ratios generally favor halving. Although halving essentially operates on affine coordinate representations, we adapt an algorithm of Knuth to allow efficient use of projective coordinates with halving-based windowing methods for point multiplication.