Lecture12

Lecture12 - Lecture 12: Discrete Logarithms, RSA,...

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Calculating Modular Exponents Before we move on, one quick note about computation. Let's consider the amount of work involved in exponentiation: Consider calculating a n-1 (mod n), for a large value of n, perhaps with about 100 bits. An iterative algorithm where you successively multiply values of a to an accumulator variable won't suffice. However, fast exponentiation, will work: Power(base, exp, mod) { if (exp == 0) return 1; if (exp == 1) return base%mod; if (exp%2 == 0) { int temp = Power(base, exp/2, mod); return (temp*temp)%mod; } return (base*Power(base, exp-1, mod))%mod; } Basically, what we do here is cut our exponent down by half for each two iterations of this algorithm. That means that we will do the operation of multiplying and modding only about 200 times at most if n is 100 bits, as opposed to doing it 2 100 times which is far worse. For a quick analysis of the time complexity, multiplying two integers of n bits takes O(n 2 ) and we will do this O(n) times in fast exponentiation for a total time of O(n 3 ) in the number of bits of the numbers being multiplied. If n is the number itself, then the amount of time is O(log 3 n). Discrete Logs A normal logarithm is defined as follows: log b a = c is equivalent to the exponential statement b c =a. Basically, if you are given a and b, you have to determine which power to raise b to in order to get the result a. This is easy to do for real numbers, but difficult to do with integers in a field mod p.
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Lecture12 - Lecture 12: Discrete Logarithms, RSA,...

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