Shereshik

The authors propose an algorithm for hashing data, basing on the increase in entropy during simulation of physical processes. The two-dimensional Ising model was selected as a system. The Ising model was studied with the use of the Metropolis algorithm. A computer experiment was carried out in order to detect collisions and determine the avalanche effect. The model’s preferred parameters such as temperature and size were identified experimentally. It was shown that the avalanche effect becomes large enough when the temperature is higher than the critical one by 28%. The dimension of the system must be chosen depending on the size of the output digest. It was also shown that the two-dimensional Ising model has sufficient mixing properties for cryptographic hash functions. The authors conducted a comparison with common algorithms MD5 and SHA-1. The developed hash algorithm is scalable, unlike traditional hash algorithms.

The authors researched sensitivity of the Metropolis algorithm for the three-dimensional Ising model to the choice of a pseudorandom sequence generator. The authors show that shortcomings of pseudorandom sequence statistical properties result in the behavior of the Ising model that differs from the one predicted by methods of theoretical physics. It is shown that the Ising model can be used for testing pseudorandom sequence generators.