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If the pad has 999,999 bits of entropy, evenly distributed (each individual bit of the pad having 0.999999 bits of entropy) it may provide good security. But if the pad has 999,999 bits of entropy, where the first bit is fixed and the remaining 999,999 bits are perfectly random, the first bit of the ciphertext will not be encrypted at all.
In this case, the entropy is maximum at a value of 1 bit. Intermediate values fall between these cases; for instance, if p = 1 / 4 {\displaystyle p=1/4} , there is still a measure of uncertainty on the outcome, but one can still predict the outcome correctly more often than not, so the uncertainty measure, or entropy, is less than 1 full bit.
where is the probability of the message taken from the message space M, and b is the base of the logarithm used. Common values of b are 2, Euler's number e, and 10, and the unit of entropy is shannon (or bit) for b = 2, nat for b = e, and hartley for b = 10. [1]
where U is the unicity distance, H(k) is the entropy of the key space (e.g. 128 for 2 128 equiprobable keys, rather less if the key is a memorized pass-phrase). D is defined as the plaintext redundancy in bits per character. Now an alphabet of 32 characters can carry 5 bits of information per character (as 32 = 2 5).
The entropy is maximized at 1 bit per trial when the two possible outcomes are equally probable, as in an unbiased coin toss. If one transmits 1000 bits (0s and 1s), and the value of each of these bits is known to the receiver (has a specific value with certainty) ahead of transmission, it is clear that no information is transmitted.
Entropy equivalent of one bit of information, equal to k times ln(2) [1] 10 −23: 1.381 × 10 −23 J⋅K −1: Boltzmann constant, entropy equivalent of one nat of information. 10 1: 5.74 J⋅K −1: Standard entropy of 1 mole of graphite [2] 10 33: ≈ 10 35 J⋅K −1: Entropy of the Sun (given as ≈ 10 42 erg⋅K −1 in Bekenstein (1973 ...
An essential characteristic of the typical set is that, if one draws a large number n of independent random samples from the distribution X, the resulting sequence (x 1, x 2, ..., x n) is very likely to be a member of the typical set, even though the typical set comprises only a small fraction of all the possible sequences.
Shannon entropy (information entropy), being the expected value of the information of an event, is inherently a quantity of the same type and with a unit of information. The International System of Units, by assigning the same unit (joule per kelvin) both to heat capacity and to thermodynamic entropy implicitly treats information entropy as a quantity of dimension one, with 1 nat = 1.