We all know that random number generation in computers is a never-ending cycle of chasing true randomness. We are trying different variables that can be recorded in the users machine to find the optimal solution to the problem of randomness. We will be combining these factors with popular Pseudorandom Algorithms to find the best algorithm we can design.
- Users MAC address
- Users Time
- Users amount of space on computer
- Users battery life
- Users' System Memory Value (GB)
- Random day in time - amount of rain fallen on that day.
- Two rain drop falling - distance between two points.
- MANY MORE TO COME.
Using the time subtracted by an arbitrary value n has worked well for finding a Psuedorandom seed value for the Marsenne Twister Algo. Finding the seed is one of the keys to unlocking a more random generator that can be used as random data to plug-in to other random algorithms such as WELLRNG512a.
This project and the implementation of the Marsenne Twister Algorithm was provided by yinengy on GitHub.
Current implementation includes a Marsenne twister by calling class Random() which is seeded by the users' time multiplied by the amount of memory their system has. This causes a different seed number everytime it is ran even at the same exact time on different machines.
>>rand = Random()
>>rand.random() or rand.randint()We also have have WELLRNG512a implemented using random data for the initial array from the new random algo from the Marsenne Twister.
>>rand = WellsRandom()
>>rand.InitWELLRNG512a()
>>rand.WELLRNG512a()Recently implemented was the Blum Blum Shub Algorithm which can be used as follows:
>>test = RandomBBS() OR RandomBBS(p,q,s)
#p and q are prime numbers and s being a seed
>>test.getRandBit()#returns a random bit(0 or 1)
>>test.setP()#set the p value(int)
>>test.setQ()#set the q value(int)
>>test.setSeed()#set the seed value(int)
>>test.getRandNumber()#returns random intWe have also included the Blum-Micali algorithm with a few helpful methods which are laid out as follows:
>>test = RandomBM()
>>test.getRandBits(n)#returns a random string of bits of length n
>>test.setSeed()#set the seed value(int)
>>test.binaryToDecimal()#takes a string binary representation and converts it to decimal(string)
>>test.getRandNumber()#returns a random int
>>test.getRandSetNum(a)#returns a random int between 0-a(int)More algorithms to come. Enjoy!
Most of these algorithms were adapted from other languages or pseudo code. Here are a few developers whose code has allowed me to create this repository. If you would like me to take down any code, please contact me.
Blum-Blum-Shub: OverStruck GitHub: https://github.com/OverStruck/blum-blum-shub-prbg
Blum-Micali: andreigasparovici GitHub: https://gist.github.com/andreigasparovici/7241fcafcfbde1edf07dad318d3fe040
Mersenne Twister: yinengy GitHub: https://github.com/yinengy/Mersenne-Twister-in-Python