23,698 reputation
23199
bio website
location Paris, France
age
visits member for 3 years, 7 months
seen 7 hours ago

I'm an engineer with experience in applied cryptography, in particular in Smart Card systems.


9h
awarded  Nice Answer
21h
revised The effect of truncated hash on entropy
polish
21h
revised The effect of truncated hash on entropy
fix sign
21h
revised The effect of truncated hash on entropy
Simplify
1d
comment The effect of truncated hash on entropy
@D.W.: given your long-running interest in entropy loss by iterated hashing, you might like this which solves the question for the first iteration (asymptotically, and in practice). Also, it shows we can numerically explore the first few iterations, and the reference I cite gives estimates.
1d
revised The effect of truncated hash on entropy
Link to thesis
1d
revised The effect of truncated hash on entropy
Link to author's webpage, fix gender
1d
revised The effect of truncated hash on entropy
Give the entropy before tuncation
1d
revised The effect of truncated hash on entropy
polish
1d
answered The effect of truncated hash on entropy
1d
comment The effect of truncated hash on entropy
@Stephen Touset: if your split a string of independent random bits (with even distribution, or at least the same distribution for all bits), then the entropy spreads evenly. However if the bits are correlated, the sum of the entropy in each half can be greater that the original entropy. In the extreme example of a two-bit string where the first bit is drawn by coin toss, and the second bit decided as the opposite of the first, there's one bit of entropy in the whole string, in the first bit, and in the second bit.
1d
comment Collision attacks on digital signatures
@René G: it is intractable to factor the 2048-bit product of two unknown random 1024-bit primes; however there is sizable hope to factor a random 2048-bit integer with moderate effort.
2d
comment The effect of truncated hash on entropy
The reasoning that keeping half the bits keeps half of the entropy is wrong, because the 256 bits of the hash of a 128-bit string are far from random. There is marginally less entropy in the hash truncated to 128 bits than there is in the 256-bit hash. Analogy: if you take the 2-bit hash that hashes 0 to 01 and 1 to 10, there's 1 bit of entropy in the output for random input. Truncate that to the first bit, and you still have 1 bit of entropy in its output.
2d
comment The effect of truncated hash on entropy
Related to this. It does not change the problem that you use a 256-bit hash truncated to 128 bits, or a 128-bit hash. The entropy is slightly reduced from the original 128 bits, because of the collisions in the 128-bit hash; there are almost no collisions in the 256-bit hash.
2d
comment Can machine learning analyze random number generator?
Are you asking if machine learning could analyze THE OUTPUT of a (P)RNG? Or if machine learning could analyze THE DEFINITION of a PRNG?
2d
revised zendo data size restrictions
Addition per comment
Mar
25
comment Cycles in SHA256
First statement is wrong.
Mar
25
comment RSA weak padding
Your $f(x)=(1+2^8+2^{16}+2^{24})\times x=K\times x$ is restricted to $x$ an at-most-8-bit element of $\mathbb N$, and has $K$ and $f(x)$ in $\mathbb N$, is not it?
Mar
25
answered Cycles in SHA256
Mar
25
revised zendo data size restrictions
polish