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4

Who can tell when my machine was booted? Anyone who observed it go on, at least. That could include someone sniffing your wlan traffic. However, if the computer in question is a shared server, anyone with access can probably call uptime. After all, /dev/random uses timings for it's cryptographically secure output. In setups where timing ...

3

I'll formalize things a bit, because I think it is then easier to understand what is going on. Definitions. A random variable $X$ is defined by a set of possible events $(x_1,...,x_n)$ and the probabilities of these events $P(x_1),...,P(x_n)$, and its entropy is defined as$$H(X):=-\sum_{i=0}^n P(x_i)\cdot \log_2(P(x_i)) \mbox{ bits}.$$ When all events have ...

8

For RSA, the answer whether it is feasible for a single computer depends on the reason your generating them (and specifically, whether they need to remain secure if you publish a number of them). For example, if you're generating the RSA keys to search for some criteria (e.g. the hash of the public key has a specific pattern), and you'll discard the ones ...

10

It is feasible to generate 300 million public key pairs of reasonable strength in 8 hours on a single computer, easily with ECDSA using a single core/thread, and even with DSA using quite a common multi-core computer. RSA would require many standard computers (baring hardware accelerators for modular exponentiation), assuming all the public keys are made ...

18

On the other hand, the Shannon entropy of a 6-sided die tossed 100 times is $-6 × 1/6 × \log_2(1/6) = 2.5849625007$ bits. That is wrong: $-6\cdot\frac16\cdot\log_2\frac16$ is the entropy of a single die roll. Assuming the $100$ die rolls are independent, you can simply sum the entropies of the individual rolls to obtain  100 \cdot\left(-6 ...

10

It seems that with your shannon entropy, you are using 100 tosses to estimate the shannon entropy of a single die toss. If it is a fair die, that would be $\log_2{6}\approx 2.58$. This is different from rolling a die 100 times to generate a cryptographic key, for example. Each roll of the fair die would contain $2.58$ bits of entropy, so in total you would ...

1

When you start chopping off bits of a SHA-256 hash, you obtain a NoSHA-256 :) hash that has none of the security properties of the original hash. I assume, however, that this is not really important in the context of your database. You can compute the probability to have a collision using the birthday paradox. If you only want 64 bits, you may prefer to ...

7

Assuming the hash function is good, and SHA256 is widely believed to be so, the probability of no collisions in $k$ samples into a range of size $n$ (e.g., obtained by selecting a subset of characters) is upper bounded by $exp(-k^2/2n).$ For you, say $k=2^{21}=2,097,152$ (couple million) and $n=2^{64}$ means that your probability of no collision is roughly ...

2

Most microcontrollers that are suitable for crypto I've seen have a variant with a hardware RNG. For example the PIC32 series by Microchip. However, if not, what you could do is attaching some sensor to an ADC. It would depend on your environment what kind of sensor you could use. It can be anything, which is not easily manipulated (at least not in the ...

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