Abstract
Cryptanalytic time memory tradeoff algorithms are tools for inverting one-way functions, and they are used in practice to recover passwords that restrict access to digital documents. This work provides an accurate complexity analysis of the perfect table fuzzy rainbow tradeoff algorithm. Based on the analysis results, we show that the lesser known fuzzy rainbow tradeoff performs better than the original rainbow tradeoff, which is widely believed to be the best tradeoff algorithm. The fuzzy rainbow tradeoff can attain higher online efficiency than the rainbow tradeoff and do so at a lower precomputation cost.
Highlights
Cryptanalytic time memory tradeoff algorithms are tools for inverting generic one-way functions
After a one-time precomputation phase, whose computational complexity order is typical as that of an exhaustive computation of the one-way function on all inputs under consideration, a digest of the computation is written to a table of size that is of much smaller order than the complete dictionary
In the online phase, referencing the precomputation table, the input corresponding to a given inversion target is recovered with a computational complexity that is of much smaller order than that of an exhaustive trial of inputs
Summary
Cryptanalytic time memory tradeoff algorithms are tools for inverting generic one-way functions. Our previous work [9] gave an accurate performance analysis of the nonperfect table fuzzy rainbow tradeoff and compared the results with the performances of the original nonperfect and perfect table rainbow tradeoffs, which are widely believed to be the best tradeoff algorithms. The fuzzy rainbow tradeoff, as originally presented by [4, 5], was a tradeoff algorithm designed to be used in the multitarget setting This is where the attacker is given multiple inversion targets and is deemed successful if he is able to recover the input corresponding to at least one of targets. We have done some preliminary investigations and believe that it will not be difficult to transform the existing analysis results for the Hellman and distinguished point algorithms that were claimed for the single-target setting and the results of the present paper to the multitarget setting.
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