On Independence and Sensitivity of Statistical Randomness Tests

Turan, Meltem Soenmez
Doğanaksoy, Ali
Boztas, Serdar
Statistical randomness testing has significant importance in analyzing the quality of random number generators. In this study, we focus on the independence of randomness tests and its effect on the coverage of test suites. We experimentally observe that frequency, overlapping template, longest run of ones, random walk height and maximum order complexity tests are correlated for short sequences. We also proposed the concept of sensitivity, where we analyze the effect of simple transformations on output p-values. We claim that whenever the effect is significant, the composition of the transformation and the test may be included to the suite as a new test.


Alternative Approach to Maurer's Universal Statistical Test
Tezcan, Cihangir; Doğanaksoy, Ali (null; 2008-12-01)
Statistical tests for randomness play an important role in cryptography since many cryptographic applications require random or pseudorandom numbers. In this study, we introduce an alternative approach to Maurer’s Universal Test. This approach allows us to test short binary sequences as small as 66 bits and to choose slightly larger block sizes. Moreover, it does not have an initialization part and requires less time to test a binary sequence.
On the independence of statistical randomness tests included in the NIST test suite
SULAK, FATİH; Uğuz, Muhiddin; Koçak, Onur Ozan; Doğanaksoy, Ali (2017-01-01)
Random numbers and random sequences are used to produce vital parts of cryptographic algorithms such as encryption keys and therefore the generation and evaluation of random sequences in terms of randomness are vital. Test suites consisting of a number of statistical randomness tests are used to detect the nonrandom characteristics of the sequences. Construction of a test suite is not an easy task. On one hand, the coverage of a suite should be wide; that is, it should compare the sequence under considerati...
Koçak, Onur Ozan; SULAK, FATİH; Doğanaksoy, Ali; Uğuz, Muhiddin (2018-01-01)
Generating random numbers and random sequences that are indistinguishable from truly random sequences is an important task for cryptography. To measure the randomness, statistical randomness tests are applied to the generated numbers and sequences. Knuth test suite is the one of the first statistical randomness suites. This suite, however, is mostly for real number sequences and the parameters of the tests are not given explicitly.
On numerical optimization theory of infinite kernel learning
Ozogur-Akyuz, S.; Weber, Gerhard Wilhelm (2010-10-01)
In Machine Learning algorithms, one of the crucial issues is the representation of the data. As the given data source become heterogeneous and the data are large-scale, multiple kernel methods help to classify "nonlinear data". Nevertheless, the finite combinations of kernels are limited up to a finite choice. In order to overcome this discrepancy, a novel method of "infinite" kernel combinations is proposed with the help of infinite and semi-infinite programming regarding all elements in kernel space. Look...
On Equivalence Relationships Between Classification and Ranking Algorithms
Ertekin Bolelli, Şeyda (2011-10-01)
We demonstrate that there are machine learning algorithms that can achieve success for two separate tasks simultaneously, namely the tasks of classification and bipartite ranking. This means that advantages gained from solving one task can be carried over to the other task, such as the ability to obtain conditional density estimates, and an order-of-magnitude reduction in computational time for training the algorithm. It also means that some algorithms are robust to the choice of evaluation metric used; the...
Citation Formats
M. S. Turan, A. Doğanaksoy, and S. Boztas, “On Independence and Sensitivity of Statistical Randomness Tests,” 2008, vol. 5203, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53838.