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Unformatted text preview: ition mappings, compression, and fast Fourier transforms . The potential problem with both methods is that if there is a correlation between adjacent bits, then these methods will increase the bias. One way to correct this is to use multiple random sources. Take four different random sources and XOR the bits together; or take two random sources, and look at those bits in pairs. For example, take a radioactive source and hook a Geiger counter to your computer. Take a pair of noisy diodes and record as an event every time the noise exceeds a certain peak. Measure atmospheric noise. Get a random bit from each and XOR them together to produce the random bit. The possibilities are endless. The mere fact that a random-number generator has a bias does not necessarily mean that it is unusable. It just means that it is less secure. For example, consider the problem of Alice generating a triple-DES 168-bit key. All she has is a random-bit generator with a bias toward 0: It produces 55 percent 0s and 45 percent 1s. This means that there are only 0.99277 bits of entropy per key bit, as opposed to 1 bit of entropy if the generator were perfect. Mallory, trying to break the key, can optimize his brute-force search to try the most probable key first (000...0), and work toward the least probable key (111...1). Because of the bias, Mallory can expect to find the key in 2109 attempts. If there were no bias, Mallory would expect to make 2111 attempts. The resultant key is less secure, but not appreciably so. Distilling Randomness
In general, the best way to generate random numbers is to find a whole lot of seemingly random events and distill randomness from them. This randomness can then be stored in a pool or reservoir that applications can draw on as needed. One-way hash functions are ready-made for the job; they’re fast, so you can shovel quite a bit through them without worrying too much about performance or the actual randomness of each observation. Hash almost anything you can find that has at least some randomness. Try: — A copy...
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This note was uploaded on 10/18/2010 for the course MATH CS 301 taught by Professor Aliulger during the Fall '10 term at Koç University.
- Fall '10