58 Pa. Code § 810a.5 - Random number generator standards
(a)
The random number generator must be cryptographically strong at the time of
submission for approval. When more than one instance of a random number
generator is used in an interactive gaming system, each instance must be
separately evaluated and certified. When each instance is identical but
involves a different implementation within a game/application, each
implementation shall also be separately evaluated and certified. Any outcomes
from the random number generator used for game symbol selection/game outcome
determination must be shown, by data analysis and a source code read, to:
(1) Be statistically independent, unless the
submission has been approved for a persistent-state outcome
determination.
(2) Be fairly
distributed (within statistically expected bounds) over their range.
(3) Pass various recognized statistical
tests.
(4) Be cryptographically
strong.
(b) Random number
generators must adhere to standards in §
461a.7 (relating to slot machine
minimum design standards).
(c) The
gaming laboratory may employ the use of various recognized tests to determine
whether or not the random values produced by the random number generator pass
the desired confidence level of 95%. These tests include the following:
(1) Chi-square test.
(2) Equi-distribution (frequency)
test.
(3) Gap test.
(4) Overlaps test.
(5) Poker test.
(6) Coupon collectors test.
(7) Permutation test.
(8) Kolmogorov-Smirnov test.
(9) Adjacency criterion tests.
(10) Order statistic test.
(11) Runs tests (patterns of occurrences
should not be recurrent).
(12)
Interplay correlation test.
(13)
Serial correlation test potency and degree of serial correlation (outcomes
should be independent of the previous game, unless the submission has been
approved for a persistent-state outcome determination).
(14) Tests on subsequences.
(15) Poisson distribution.
(d) The scaling method may not
compromise the cryptographic strength of the random number generator. The
scaling method must preserve the distribution of the scaled values. For
example, if a 32-bit random number generator with a range of the set of
integers in the closed interval (0, 232-1) were to be
scaled to the range of the set of integers in the closed interval (1, 6) so
that the scaled values can be used to simulate the roll of a standard six-sided
die, then each integer in the scaled range should theoretically appear with
equal frequency. In the example given, if the theoretical frequency for each
value is not equal, then the scaling method is considered to have a bias. Thus,
a compliant scaling method must have bias equal to zero.
(e) If the interactive gaming system utilizes
hard-based random number generators, there must be dynamic/active, real-time
monitoring of the output with a sample size large enough to allow for
reasonably high statistically powerful testing so that game play is disabled
when an output testing failure is detected.
(f) If the interactive gaming system utilizes
a software-based random number generator, it must adhere to all of the
following:
(1) The period of the random
number generator, in conjunction with the methods of implementing the random
number generator outcomes, must be sufficiently large to ensure that all game
independent outcome combinations/permutations are possible for the given
game/application, unless the submission has been approved for a
persistent-state outcome determination.
(2) The methods of seeding/reseeding must
ensure that all seed values are determined in a manner that does not compromise
the cryptographic security of the random number generator.
(3) To ensure that random number generator
outcomes cannot be predicted, adequate background cycling/activity must be
implemented in between games. Whenever a game outcome is made up of multiple
mapped random number generator values, background cycling/activity must be
implemented during the game (that is, in between the selection of each mapped
random number generator value) to ensure that the game outcome is not comprised
of sequential mapped random number generator outcomes. The rate of background
cycling/activity must be sufficiently random in and of itself to prevent
prediction.
Notes
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