Android Open Source

  Java PRNG The Czech Entropy application has bugs fixed, conversion improved, and a second level of number generation added. The application version is currently in preparation for publication. Next, a module will be added to estimate and improve the entropy of the generated numbers. Improvement up to perfect distribution. https://drive.google.com/file/d/1in6sX45yDGty7NyDGCskZhJYJ4wo8V_T/view?usp=sharing Czech Entropy Android http://czechentropy.freetzi.com/

  Expansion of the original data   The existing version of the Czech Entropy application uses TTS to expand the source data (at each level). This makes the application sensitive to the Android version and hardware. But! A fundamental solution has been found for creating an effective module for expanding data with any coefficient. And the algorithm also depends on the Android build and the type of smartphone.  Czech Entropy  

  PRNG Quality You can graphically represent the generated array of "random" numbers.   Everything seems to be fine. But if we take two adjacent numbers together as coordinates, it might look like this   It is clear that the numbers are not random at all. Patterns. This can be in 3-dimensional space and in N-dimensional space. But we can come up with a means to compensate for the lack of a generator. We will generate few random numbers (discard a lot) and after generating each array we will change the generation algorithm (to get a different distribution). Green points. Czech Entropy PRNG Android Application        

  PRNG   The addition of neural networks can achieve advanced performance PRNG applications. And change them as many times as you like, maintaining synchronicity of work. public Double Prediction (Integer DataInput1, Integer DataInput2){     return neurons.get(5).compute(            neurons.get(4).compute(            neurons.get(2).compute(DataInput1, DataInput2),            neurons.get(1).compute(DataInput1, DataInput2)            ),            neurons.get(3).compute(            neurons.get(1).compute(DataInput1, DataInput2),            neurons.get(0).compute(DataInput1, DataInput2)      ...

  PRNG Czech Entropy "random" number generator is now fully functional. Although the quality of entropy is not high, it can be significantly improved. In addition, it is very easy to generate numbers in a different dimension. At least 64 digit numbers. Variable length numbers can be easily generated. You can configure the generation of numbers with gaps in the generation range and even with floating gaps (spaces). Moreover, all this is synchronous. Such generators must be programmed individually. The reliability of encryption greatly depends on this.   If you use a synchronous generator for encryption, there is a lot to do. There should be no more than two instances of the application. So that the application itself cannot be decoded, it is impossible to generate a large array of values and calculate the features of the program (this can be counteracted). The generator must use a neural network and train both instances of the application in the same way. The neur...

  Czech Entropy Synchronous random number generators PRNG Let's look at several ways to create software random number generators using external digital streams and without them. Let's write source code for Android Java - prototypes of applications showing the reality of using algorithms. Generator of "random" numbers using expansion of source information, sampling and correction of source data. (Czech Entropy Application) We will use TTS technology in this generator - converting the entered text into speech. This option is available in the Android operating system. TTS allows you to significantly increase the volume of data (30-100 thousand times), use different settings to obtain different digital results, ensure repeatability of the results (which makes it possible to build a PRNG ), the transformation is “formulaless”. The disadvantages of the algorithm are obvious: the result is easily repeated (if you know the source text), large but not infinite expansion of the...

  PRNG   Software random number generators (especially synchronous generators) are a very interesting topic to develop. Even if we take the Mersen twister, it repeats itself after some time. But if you randomly select numbers from this stream, the likelihood of repetition will decrease. We use the second software random number generator. If you then enter permutations of the resulting numbers, the likelihood of repetitions will further decrease. This can be done many times and use dozens of generators of dozens of types. In this case, if the procedure is the same on the transmitting and receiving sides, the same results will be obtained. Those. Synchronous generation is ensured without using an interaction channel. For such systems, you can create a specialized programming language or a set of classes and methods. Of course, Android, iOS or Windows are not the operating systems on which cryptography systems are built. But they are convenient for creating and testing ...