Pseudorandomness

Pseudorandomness is a process which has a result that seems to be random. Even if the result seems to be random, the process can be predicted.

This near random process is important to online security. Because the result can be predicted, it is important that the "seed,"(or first input) and the process are kept hidden.

 History 
The creation of random numbers has many uses, mostly in statistics, and simulations. Before computers, researchers that needed random numbers would get them from dice, cards, roulette wheels,  etc, or by random number tables.

The first attempt to crate a large amount of random numbers was in 1927. This was when Cambridge University Press put out a list of 41,600 numbers made by L.H.C. Tippett. In 1947, the RAND Corporation created random numbers by simulating a roulette wheel using a computer. The results were published in 1955 with the title of, "A Million Random Digits with 100,000 Normal Deviates".

 Unpredictability as "near random" 
By using radioactive substances with radioactive decay,  or by tuning a radio between stations, near random numbers can be created for short amounts of time. The time needed to get these numbers led to a change. This was using these generated numbers as a "seed" instead of a result.  The less numbers created by this process, the more random the result would seem. Another compromise is to combine the timings between keystrokes of multiple people.

People's actions have been proven to be useful for Multi-factor authentication. Also, studies have shown that pseudo random numbers can sometimes be predicted. This becomes more difficult when in small amounts.

 In computational complexity 
In theoretical computer science, a distribution (set of numbers) is considered to be pseudorandom if it is similar enough to other sets. This idea of pseudorandomness is studied and has importance in cryptography.

 Related pages 

 Pseudorandom number generator
 Random

 References 

 Further reading 

 Donald E. Knuth (1997) The Art of Computer Programming, Volume 2: Seminumerical Algorithms (3rd edition). Addison-Wesley Professional, 
 Oded Goldreich. (2008) Computational Complexity: a conceptual perspective. Cambridge University Press. .   


Category:Theoretical computer science