RNG CASINO report need the technical knowledge decoded
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£300(approx. $376)
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Description
Experience Level: Expert
I have purchased a copy of the latest REPORTS/INTEL, explaining how the RNG in casino's work and the flaws in them. I have very little expertise with regards to the mathematical/software programming language that has been used, so if anyone has an idea i would be greatful if they could help me decode this into simpler terms, and possibly write a system for placing bets.
The document contains Random number generator facts, A Software Library in ANSI C for Testing of Random Number Generators, and a report on RNG.
Example of language used,
'Every empirical test is a simulation. If selected with care, then a particular test will cover a whole class of simulation problems. Nothing can be deduced from the results of an empirical test if the practitioner uses completely different parameters in his own simulation problem. In contrast to theoretical tests, empirical tests treat the random number generators as black boxes and do not directly analyze the underlying algorithm. This makes it possible to observe the performance for smaller and larger parts of the period.
In cryptography, as soon as we can distinguish a given bitstream from the output of a "perfect random source", attacks to the algorithm will be possible. The difficulty is to find such distinguishers and to mount an efficient attack. Use the Report that tests every RNG to help you understand the RNG in full facts.'
Thanks to anyone who can help
The document contains Random number generator facts, A Software Library in ANSI C for Testing of Random Number Generators, and a report on RNG.
Example of language used,
'Every empirical test is a simulation. If selected with care, then a particular test will cover a whole class of simulation problems. Nothing can be deduced from the results of an empirical test if the practitioner uses completely different parameters in his own simulation problem. In contrast to theoretical tests, empirical tests treat the random number generators as black boxes and do not directly analyze the underlying algorithm. This makes it possible to observe the performance for smaller and larger parts of the period.
In cryptography, as soon as we can distinguish a given bitstream from the output of a "perfect random source", attacks to the algorithm will be possible. The difficulty is to find such distinguishers and to mount an efficient attack. Use the Report that tests every RNG to help you understand the RNG in full facts.'
Thanks to anyone who can help
David W.
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