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5

As fgrieu notes in the comments, the protocol might not even work reliably in the absence of adversaries: if the tag fails to receive the reader's reply of "True", the keys will get out of sync. (If that happens, the tag will just retry the next exchange with the old key, so this could be fixed by having the reader remember one more "subkey". But the ...


5

My experience of such proofs is that often you're proving a much stronger statement: in any execution of Game i+1, either everything is distributed identically to Game i or else F must have happened. In other words, the conditional distribution of game i+1 conditioned on F not happening is identical to the distribution of Game i. For example, one of ...


3

Ok, here's a version that definitely works. Three points: If we know $S_2$ is close to $1/2$, then the statement that $S_1$ and $S_2$ are close is equivalent to saying that $S_1$ is close to $1/2$. So I'll prove the latter version. The way to deal with the edge cases, I think, is to demand Pr$[S_2|F] = 1/2$. This is the case whenever the game (not the ...


3

However I think that the requirement on $\Pr[F]$ is way too strong: one can prove security with much more frequent faults. Maybe this short paper by Alexander W. Dent could be of interest: A Note On Game-Hopping Proofs? In this paper he introduces a fourth kind of game hop, namely transitions based on large failure events, which seems to be exactly what ...


2

Assuming that the probability distributions of $\pi_{k_1}$ and $\pi_{k_2}$ are both uniform (that is, each permutation can take on any particular setting with probability $1/n!$), then no, adversary does not have enough information to learn anything about the original positions. This remains true even if we assume the adversary can perform unbounded ...



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