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True Random Number generation |
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LavaRnd is a cryptographically sound random number generator. At its heart, it uses a chaotic source to power the generation of very high quality random numbers. |
LavaRnd is a cryptographically sound random number generator. At its heart, it uses a chaotic source to power the generation of very high quality random numbers. |
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General process |
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LavaRnd turns real world physical chaotic events into random numbers in 3 stages: |
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1. Digitization of a chaotic source: |
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A digital snapshot of a physical chaotic process is obtained. Any chaotic source that is sensitive to measurement errors can be used. The Heisenberg Uncertainty Principle suggests that you cannot measure, with perfection, any chaotic source. If the chaotic source you choose is driven by quantum events then recreating the chaotic source is impossible. Moreover, chaos will render any simulation useless as a means to predict future conditions. |
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2. Digital Blender (tm) |
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The digital snapshot containing both structured data and chaotic noise is run through a Digital Blender Algorithm. The combination of n different SHA-1 cryptographic hash operations running in parallel, and n different xor-rotate and fold operations on data containing some chaotic noise destroys the structured data portion of the digital snapshot and produces uniformly distributed random data. |
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3. Presentation: |
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The uniformly distributed random data is collected into a pool and used only once to produce random values in the form required by the application. |
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* http://www.lavarnd.org/what/index.html |
* http://www.lavarnd.org/what/index.html |
Latest revision as of 15:41, 11 June 2005
True Random Number generation
LavaRnd is a cryptographically sound random number generator. At its heart, it uses a chaotic source to power the generation of very high quality random numbers.
General process
LavaRnd turns real world physical chaotic events into random numbers in 3 stages:
1. Digitization of a chaotic source:
A digital snapshot of a physical chaotic process is obtained. Any chaotic source that is sensitive to measurement errors can be used. The Heisenberg Uncertainty Principle suggests that you cannot measure, with perfection, any chaotic source. If the chaotic source you choose is driven by quantum events then recreating the chaotic source is impossible. Moreover, chaos will render any simulation useless as a means to predict future conditions.
2. Digital Blender (tm)
The digital snapshot containing both structured data and chaotic noise is run through a Digital Blender Algorithm. The combination of n different SHA-1 cryptographic hash operations running in parallel, and n different xor-rotate and fold operations on data containing some chaotic noise destroys the structured data portion of the digital snapshot and produces uniformly distributed random data.
3. Presentation:
The uniformly distributed random data is collected into a pool and used only once to produce random values in the form required by the application.