Kim, Hae Young; Park, Jung Youl; Cheon, Jung Hee; Park, Je Hong; Kim, Jae Heon; Hahn, Sang Geun Fast elliptic curve point counting using Gaussian normal basis. (English) Zbl 1058.11075 Fieker, Claus (ed.) et al., Algorithmic number theory. 5th international symposium, ANTS-V, Sydney, Australia, July 7–12, 2002. Proceedings. Berlin: Springer (ISBN 3-540-43863-7). Lect. Notes Comput. Sci. 2369, 292-307 (2002). Summary: In this paper we present an improved algorithm for counting points on elliptic curves over finite fields. It is mainly based on Satoh-Skjernaa-Taguchi algorithm [T. Satoh, B. Skjernaa and Y. Taguchi, Finite Fields Appl. 9, No. 1, 89–101 (2003; Zbl 1106.14302)], and uses a Gaussian Normal Basis (GNB) of small type \(t\leq 4\). In practice, about 42% (36% for prime \(N\)) of fields in cryptographic context (i.e., for \(p=2\) and \(160< N<600\)) have such bases. They can be lifted from \(\mathbb {F}_{p^N}\) to \(\mathbb {Z}_{p^N}\) in a natural way. From the specific properties of GNBs, efficient multiplication and the Frobenius substitution are available. Thus a fast norm computation algorithm is derived, which runs in \(O(N^{2\mu} \log N)\) with \(O(N^{2})\) space, where the time complexity of multiplying two n-bit objects is \(O(n^\mu)\). As a result, for all small characteristic \(p\), we reduced the time complexity of the SST-algorithm from \(O(N^{2\mu + 0.5})\) to \(O(N^{2\mu + \frac{1}{\mu + 1}})\) and the space complexity still fits in \(O(N^{2})\). Our approach is expected to be applicable to the AGM since the exhibited improvement is not restricted to only Satoh-Skjernaa-Taguchi (loc. cit.).For the entire collection see [Zbl 0992.00024]. Cited in 4 Documents MSC: 11Y16 Number-theoretic algorithms; complexity 11G20 Curves over finite and local fields 12Y05 Computational aspects of field theory and polynomials (MSC2010) Keywords:elliptic curve; Gaussian normal basis; order counting PDF BibTeX XML Cite \textit{H. Y. Kim} et al., Lect. Notes Comput. Sci. 2369, 292--307 (2002; Zbl 1058.11075) Full Text: Link