# Tag Info

74

"lucky" is not a property of the attacker. There's no "lucky" attacker nor "normal" attacker. They both have the same probability (low, very low) to guess the key. You can decrease the probability at will by increasing the length of the key (i.e. the no. of bits). You cannot really argue "what if the attacker is lucky" because "being lucky" is a posteriori ...

42

Note: This answer assumes that by "lucky" OP meant "able to remove X% of valid answers", because I believe that was intent. Of course you can't measure luck ;) And if he is very lucky, say 90% chance, that means that 1 bit is actually only 0.1 bit.So in face of a very lucky opponent, a 128 bit password has only 12.8 bit strength. Well, let's validate ...

38

If you repeatedly apply a generic function on its result, in a finite domain, you tend to obtain a "rho" structure: at some point, you enter a cycle whose length is (roughly) $\sqrt{N}$, where $N$ is the size of the output space for your function. In the case of MD5, $N = 2^{128}$ (MD5 outputs 128-bit values), so the cycle will have length about $2^{64}$ ...

33

You are likely going to have both false positives and false negatives if you try to use Shannon entropy for this. Many compressed files would have close to 8 bits of entropy per byte, resulting in false positives. Any encrypted file that has some non-binary encoding (like a file containing an ASCII-armored PGP message, or just a low entropy header) could ...

25

So if at each bit he has a 50% chance, that means that 1 bit is actually only half bit. And if he is very lucky, say 90% chance, that means that 1 bit is actually only 0.1 bit.So in face of a very lucky opponent, a 128 bit password has only 12.8 bit strength. You're miscomputing how "luck" affects the number of bits. For a 50% chance, that does not ...

23

I don't get nearly the amount of entropy stated in the comic. Interestingly enough the reasoning for the entropy rating are actually justified in the comic by the little boxes which each represent 1 bit of uncertainty. This means for Tr0ub4dor&3 It's estimatated that the word itself "Troubador" comes up in dictionaries which contain about $2^{16}$ ...

21

First of all, there is a difference between writing to /dev/random and/or /dev/urandom and increasing the entropy count maintained in the Kernel. This is the reasony why, by default, /dev/random is world-writable - any input will only augment, but never replace the internal state of the RNG; if you write completely predictable data, you're doing no good, ...

21

You've actually been trapped by the mindset that OTP will hide all information about the underlying plaintext. This is not true as you have observed. The definition of perfect secrecy, given in Introduction to Modern Cryptography by Katz-Lindell, reads like this: Definition 2.3 An encryption scheme $(\text{Gen, Enc, Dec})$ with message space $\mathcal M$...

20

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 \cdot\frac16\... 19 I will answer considering Linux OS, as being one of most popular Unix-like OS (between OSes which have urandom). If you need other OS, please, inform me. Also I will answer using source code of random.c driver from Linux 3.3.3 Kernel, because it is one of best documentation of /dev/random mechanics. And the other is paper: Analysis of the Linux Random Number ... 19 Entropy is a function of the distribution. That is, the process used to generate a byte stream is what has entropy, not the byte stream itself. If I give you the bits 1011, that could have anywhere from 0 to 4 bits of entropy; you have no way of knowing that value. Here is the definition of Shannon entropy. Let X be a random variable that takes on the ... 19 The answer rather depends on what you mean by 'entropy'; if you mean 'Shannon Entropy', then no, a deterministic function cannot increase entropy. For example, if the unhashed password has only 7 different possible values, then the hashed version of the password will also have (at most) 7 different possible values; you've made things look more obscure, but ... 19 You're absolutely correct: numbers (or a given binary string) don't have entropy. However, a number can be sampled from a distribution that has entropy. In other words, the entropy is a property of the process used to generate a number, not of the number itself. So if I just give you the number 4, and assure you that I picked this number uniformly at random ... 19 Even in context, much of what is written in the blog post makes no sense. E.g., it says: While it can be argued that the DRNG is in reality just splitting a 128-bit value into two pieces and handing them to you one piece at a time, from a theoretical viewpoint this does not matter. While the original value had 128 bits of entropy, the end result is that ... 18 First let's say that entropy is a property of a generation process. A number, by itself, does not have any entropy. What has entropy is the algorithm or process which has produced that number, and the entropy measures what the number could have been. In that sense, the formulation in the Wikipedia page lacks rigour. For a "nothing up my sleeve" number, we ... 17 A simple way to imagine the effect of the hash function is a truncation. A "good" hash function ought to behave like a random oracle. If your source has entropy s bits, then this means that the source somehow assumes 2^s possible values. When processed with a random oracle with an n-bit output, you force the 2^s input values into 2^n possible ... 17 Very short answer: No Quite Short answer: No, because a scheme can only be a One-Time-Pad if the entire pad is perfectly random and secret. Concise answer: It sounds like you're trying to build a stream cipher. The security of it really comes down to how much of the scheme you think can be kept secret. If I listen in to your wifi and hear you requesting a ... 17 If one source remains uncompromised plus statistically random on all bits, and both sources remain independent, then a xor of both sources together can also be considered uncompromised plus statistically random for all bits. Basic proof: Label the the results two RNGs X and Y, consider bits X_n, Y_n and Z_n = X_n \oplus Y_n Assume each value of ... 17 Is it possible to securely transfer random values in such a way that they are still viable for use in cryptography? Yes and this is done all the time. If you use a TLS_RSA cipher suite, the client uses RSA to encrypt key material, i.e. random values, and transfer that securely to the server for key derivation. The owner of the random.org service ... 16 Update: Since I wrote this post, CryptGenRandom has been deprecated. Apparently it is now recommended to use BCryptGenRandom from the "Cryptography Next Generation" API. (Confusingly, it has nothing to do with bcrypt.) Yes, Windows has something similar. It can be accessed through CryptGenRandom. With Microsoft CSPs, CryptGenRandom uses the same random ... 15 Well, your definition of entropy is known as Kolmogorov complexity, and it's not so much that it is incorrect, as it is that it is inapplicable to what gzip does. For example, the value \pi can also be generated by a short program; however, if you attempt to compress a 2.2Mbyte sample of the binary expansion, you'll also find that gzip will also not be ... 15 I'm not sure what you're trying to understand and if the other answers cover it, so I'm trying a different approach and interpret your question like this: What if an attacker guesses the right sequence of 128 bits on her first try by pure chance? That's certainly possible but so unlikely that we don't normally consider that possibility. If you want to ... 14 The entropy for the output of SHA-256 truncated to its first 128 bits when fed a random 128-bit input is about 127.173 bit, down from very close to 128 bit before truncation (see final note). The truncation does not halve the entropy, because the halves are not independent. The right line of thought is that SHA-256 truncated to its first 128 bits ... 13 No. This is not safe. The one-time pad requires that the pad be generated by a true-random process, where each bit of the pad is chosen uniformly at random (0 or 1 with equal probability), independent of all other bits. Any deviation from that, and what you haven't is no longer the one-time pad cryptosystem -- it is some kludgy thing. In particular, once ... 13 I know that humans would find it impossible to maintain a 128 bit password -- however, I wonder if there is some technical reason why a 52 bit password would not be as weak as a 52-bit encryption key for that matter. First, I would argue that 128 bits is not impossible to remember. My current password manager master password is almost 100 bits (6 words from ... 13 If the source as 3 entropy bits per 1024 source bits, constructing a 128-bit seed requires \lceil128\cdot 1024/3\rceil=43691 source bits at least. The "XOR 350 bits with jump 128 bits" translates to (correcting the question's formula)$$o_i=n_i\oplus n_{i+128}\oplus n_{i+2\cdot128}\oplus n_{i+3\cdot128}\oplus\dots\oplus n_{i+348\cdot128}\oplus n_{i+349\...

12

Assuming the n-bit CRC of an unknown bit string b is known, one can constructively rebuild any consecutive n bits of b from the rest of the bit string (and the definition of the CRC). Indeed, in the case described, that speeds up password search considerably. One can compute the last 32 bits of the password (likely, 4 characters) from the beginning of the ...

12

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 ...

12

How much entropy is enough? For a password, something around truly 96-bits of entropy is enough. After all password usually go through some slow password hashing which increases the work load for attacks significantly. And even with a super-fast verification function 96-bit should be just out of reach of attackers. How much is overkill? Going above 500-...

12

Assuming that $b = 2^k-1$ for some positive integer $k$, XORing two (or more) numbers in the range $[0,b]$ will indeed yield a number in the same range. If the numbers are random, uniformly distributed over the range and independent, then the result will also be random and uniformly distributed. In fact, we can even prove a stronger result saying that if ...

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