See Guesswork is not a substitute for Entropy for one discussion of this.įor how this does and doesn't apply to thermodynamics more broadly (and particularly how it applies to the famous Maxwell's Demon), I recommend the Wikipedia article comparing the two kinds of entropy. This is not true in any useful way, and certainly not like heat energy.Īlso, how cryptographers use the word entropy isn't precisely the same as how Shannon used it. Conversely, information entropy is sometimes incorrectly thought of as a form of energy that is "depleted" when generating random numbers. In particular, one is almost exclusively interested in entropy gradients in thermodynamics, while entropy is treated as an absolute value in information theory (measured in bits). You must be careful at this point not to over-analogize between thermodynamic and information entropy. To the extent that this random number is predictable (has low entropy), the system is weakened. A good crypto system will include a high-entropy value like a well-seeded and unpredictable random number. Systems whose highest-entropy input is a human chosen password are going to be very poor crypto systems because they are very predictable (have little information low entropy). The output of a cryptographic algorithm can have no more entropy than its highest-entropy input. Allotropes: the more ordered forms have lower S. The third law of thermodynamics establishes the zero for entropy as that of a perfect, pure crystalline solid at 0 K. If Suniv < 0, the process is nonspontaneous, and if Suniv 0, the system is at equilibrium. The reason all of this plays into cryptography is because the goal of a cryptographic system is generate an output that is indistinguishable from random, which is to say that it takes low-entropy information and outputs high-entropy information. Therefore graphite has a higher standard entropy than diamond. The second law of thermodynamics states that a spontaneous process increases the entropy of the universe, Suniv > 0. But if I know that you will be sending me the digits of pi, then the digits themselves have zero information because I could have computed all of them myself. The digits of pi have very high entropy because an arbitrary one is impossible to predict (assuming pi is normal). It also means that the amount of entropy is highly dependent on context. Similarly, a good random number generator is defined by having very high entropy/information/surprise. Systems with low entropy are easy to compress, because you can predict what comes next given what you've seen before.Ĭounter-intuitively, this means that a TV showing static (white noise) is presenting a lot of information because each frame is random, while a TV show has comparatively little information because most frames can be mostly predicted based on the previous frame. Systems with high entropy are difficult to compress, because every bit is surprising and so has to be recorded. A system with high entropy has a large surprise. Information entropy (also called Shannon Information) is the measure of "surprise" about a new bit of information. State Department, which adopted the BAC system in 2007, has added an anti-skimming material to electronic passports to mitigate the threat of.
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