Building Test Batteries Based on Analyzing Random Number Generator Tests within the Framework of Algorithmic Information Theory.

The problem of testing random number generators is considered and a new method for comparing the power of different statistical tests is proposed. It is based on the definitions of random sequence developed in the framework of algorithmic information theory and allows comparing the power of different tests in some cases when the available methods of mathematical statistics do not distinguish between tests. In particular, it is shown that tests based on data compression methods using dictionaries should be included in test batteries.

Unconditionally Secure Ciphers with a Short Key for a Source with Unknown Statistics.

We consider the problem of constructing an unconditionally secure cipher with a short key for the case where the probability distribution of encrypted messages is unknown. Note that unconditional security means that an adversary with no computational constraints can only obtain a negligible amount of information ("leakage") about an encrypted message (without knowing the key). Here, we consider the case of a priori (partially) unknown message source statistics.

Information-Theoretic Method for Assessing the Quality of Translations.

In recent years, the task of translating from one language to another has attracted wide attention from researchers due to numerous practical uses, ranging from the translation of various texts and speeches, including the so-called "machine" translation, to the dubbing of films and numerous other video materials. To study this problem, we propose to use the information-theoretic method for assessing the quality of translations. We based our approach on the classification of sources of text variability proposed by A.

Using Data Compression to Build a Method for Statistically Verified Attribution of Literary Texts.

We consider the problems of the authorship of literary texts in the framework of the quantitative study of literature. This article proposes a methodology for authorship attribution of literary texts based on the use of data compressors. Unlike other methods, the suggested one gives a possibility to make statistically verified results.

Time-Adaptive Statistical Test for Random Number Generators.

The problem of constructing effective statistical tests for random number generators (RNG) is considered. Currently, there are hundreds of RNG statistical tests that are often combined into so-called batteries, each containing from a dozen to more than one hundred tests. When a battery test is used, it is applied to a sequence generated by the RNG, and the calculation time is determined by the length of the sequence and the number of tests.