@MISC{Joux_1, author = {Antoine Joux and Stefan Lucks}, title = {1}, year = {} }

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Abstract

Abstract. An r-collision for a function is a set of r distinct inputs with identical outputs. Actually finding r-collisions for a random map over a finite set of cardinality N requires at least about N (r−1)/r units of time on a sequential machine. For r=2, memoryless and well-parallelisable algorithms are known. The current paper describes memory-efficient and parallelisable algorithms for r ≥ 3. The main results are: (1) A sequential algorithm for 3-collisions, roughly using memory N α and time N 1−α for α ≤ 1/3. I.e., given N 1/3 units of storage, on can find 3-collisions in time N 2/3. Note that there is a time-memory tradeoff which allows to reduce the memory consumption. (2) A parallelisation of this algorithm using N 1/3 processors running in time N 1/3. Each single processor only needs a constant amount of memory. (3) An generalisation of this second approach to r-collisions for r ≥ 3: given N s parallel processors, on can generate r-collisions roughly in time N ((r−1)/r)−s, using memory N ((r−2)/r)−s on every processor.