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Collision of Random Walks and a Refined Analysis of Attacks on the Discrete Logarithm Problem

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9020)

Abstract

Some of the most efficient algorithms for finding the discrete logarithm involve pseudo-random implementations of Markov chains, with one or more “walks” proceeding until a collision occurs, i.e. some state is visited a second time. In this paper we develop a method for determining the expected time until the first collision. We use our technique to examine three methods for solving discrete-logarithm problems: Pollard’s Kangaroo, Pollard’s Rho, and a few versions of Gaudry-Schost. For the Kangaroo method we prove new and fairly precise matching upper and lower bounds. For the Rho method we prove the first rigorous non-trivial lower bound, and under a mild assumption show matching upper and lower bounds. Our Gaudry-Schost results are heuristic, but improve on the prior limited understanding of this method. We also give results for parallel versions of these algorithms.

Keywords

Discrete Logarithm Collision Time Step Type Discrete Logarithm Problem Potential Collision 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© International Association for Cryptologic Research 2015

Authors and Affiliations

  1. 1.Graduate School of Information Science and Electrical EngineeringKyushu UniversityFukuokaJapan
  2. 2.Department of Mathematical SciencesUniversity of Massachusetts LowellLowellUSA

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