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.[1]
This near random process is important to online security.[2] Because the result can be predicted, it is important that the "seed,"(or first input) and the process are kept hidden.[3]
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,[4] 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.[4] 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.[1] 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.[5]
People's actions have been proven to be useful for Multi-factor authentication.[6] 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
References
- ↑ 1.0 1.1 George Johnson (June 12, 2001). "Connoisseurs of Chaos Offer A Valuable Product: Randomness". The New York Times. https://www.nytimes.com/2001/06/12/science/connoisseurs-of-chaos-offer-a-valuable-product-randomness.html.
- ↑ "The inherent flaws of Proof-of-Stake". Archived from the original on 2022-04-01. Retrieved 2023-02-21.
- ↑ Mark Ward (August 9, 2015). "Web's random numbers are too weak, researchers warn". BBC. https://www.bbc.com/news/technology-33839925.
- ↑ 4.0 4.1 "A Million Random Digits". RAND Corporation. January 2001. Retrieved 2017-03-30.
- ↑ Jonathan Knudson (January 1998). "Javatalk: Horseshoes, hand grenades and random numbers". Sun Server: 16–17.
- ↑ Eze Vidra (November 6, 2007). "Science Fiction? ClassifEye's Biometric Authentication for Cell Phones".
Further reading
- Donald E. Knuth (1997) The Art of Computer Programming, Volume 2: Seminumerical Algorithms (3rd edition). Addison-Wesley Professional, ISBN 0-201-89684-2
- Oded Goldreich. (2008) Computational Complexity: a conceptual perspective. Cambridge University Press. ISBN 978-0-521-88473-0. (Limited preview at Google Books)
- Vadhan, S. P. (2012). "Pseudorandomness". Foundations and Trends in Theoretical Computer Science. 7 (1–3): 1–336. doi:10.1561/0400000010.