Approximate Entropy Time
From DiceLock.org
Contents |
Approximate Entropy
Test performed with librandomtests.so.
This is a test to analyze the relation between stream length and test time for Approximate Entropy Random Test.
Also, it allows us to set the relation between stream length, test time, randomness and errors.
The test has been performed in order to extract information for DiceLock project.
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Test performed
Test environment:
Hardware: Intel Pentium IV - 3,2 GHz, 1 GB RAM OS: Linux 2.6.18.2-34-default i686 System: openSUSE 10.2 (i586)
NIST file input stream data:
File: data.e Minimum stream length: 104 bits ( 13 bytes) Maximum stream length: 262.144 bits (32.768 bytes) Number of streams tested: 32.755 streams All streams starting from first bit of file Each stream 8 multiple
Test Time & Stream Length
The relation between Stream Length and Test Time.
Graphically:
Times for:
104 bits: 0,000000 seg. 262.144 bits: 0,050226 seg.
Regression with Weka:
Parameters:
section: functions Classifier: LinearRegression Cross-validation: 10-fold class. Test Time
Results:
=== Run information ===
Scheme: weka.classifiers.functions.LinearRegression -S 0 -R 1.0E-8
Relation: QueryResult-weka.filters.unsupervised.attribute.Remove-R1-2,4-6,8
Instances: 32641
Attributes: 2
String_Length
Test_Time
Test mode: 10-fold cross-validation
=== Classifier model (full training set) ===
Linear Regression Model
Test_Time =
(0.1996 * 10e-6) * String_Length +
-(25.7431 * 10e-6)
Time taken to build model: 0.53 seconds
=== Cross-validation ===
=== Summary ===
Correlation coefficient 0.9981
Relative absolute error 3.6283 %
Root relative squared error 6.1297 %
Total Number of Instances 32641
Test Time, Stream Length, Random & Test Errors
Graphically:
Bits streams checked below 1024 (RESULTS_INACCURATE) cannot be checked.
Bit streams checked above 1024 are random.
Errors shown:
Number 5 - RESULTS_INACCURATE
Approximate Entropy test block parameter = 5 When Approximate Entropy test block > (int)(log(Stream Length)/log(2)-5)) => RESULTS_INACCURATE
References
[NIST] National Institute of Standards and Technology.
[NIST RNGT] NIST Random Number Generation and Testing.
[Weka] Weka - collection of machine learning algorithms for data mining tasks.
[RapidMiner] Rapidminer - open-source data mining solution




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