Shuffling Cards When You Are of Very Little Brain: Low Memory Generation of Permutations
Boaz Menuhin, Moni Naor

TL;DR
This paper studies how to generate permutations with limited memory, establishing bounds on guessing success and proposing efficient methods for low-memory permutation generation, with implications for cryptography and randomness.
Contribution
It provides tight bounds on the relationship between memory size and guessing difficulty, and introduces efficient, transparent permutation generators for low-memory scenarios.
Findings
Low-memory generators limit guesser success to O(n/m + log m)
Optimal bounds are proven even with secret memory
Efficient permutation generation with constant time per turn
Abstract
How can we generate a permutation of the numbers through so that it is hard to guess the next element given the history so far? The twist is that the generator of the permutation (the ``Dealer") has limited memory, while the ``Guesser" has unlimited memory. With unbounded memory (actually bits suffice), the Dealer can generate a truly random permutation where is the expected number of correct guesses. Our main results establish tight bounds for the relationship between the guessing probability and the memory required to generate the permutation. We suggest a method for an -bit Dealer that operates in constant time per turn, and any Guesser can pick correctly only cards in expectation. The method is fully transparent, requiring no hidden information from the Dealer (i.e., it is "open book" or "whitebox"). We show that this bound is the best…
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Taxonomy
TopicsDNA and Biological Computing · Algorithms and Data Compression · Cellular Automata and Applications
