The work revealed the need for providing cryptographic protection and immunity to data transmission and control commands when using the mobile robotic platform as well as the importance of taking into account the limitations regarding dimensions, energy consumption and productivity. It was found that one of the ways to meet the requirements of cryptographic protection is the use of neuro-like networks. Their feature is the ability to pre-calculate the weight coefficients that will be used when encrypting/decrypting data. It is suggested that during neuro-like encryption/decryption of data, the key should be generated taking into account the architecture of the neuro-like network (the number of neurons, the number of inputs and their bit rate), the matrix of weight coefficients and the table for masking. It was determined that a neural network with pre-calculated weight coefficients makes it possible to use a table-algorithmic method for data encryption/decryption, which is based on the operations of reading from memory, adding and shifting. Limitations regarding dimensions, energy consumption and performance are analyzed. They can be overcome during implementation by using a universal processor core supplemented with specialized FPGA hardware for neuro-like elements. That is the combined use of software and specialized hardware ensures the effective implementation of neuro-like data encryption/decryption algorithms and management teams. Models and tools for debugging and testing a neuro-like cryptographic system are presented. A model of the preliminary settings of the neuro-like data encryption system has been developed, the main components of which are the former of the neuro-like network architecture, the calculator of weight coefficient matrices and the calculator of tables of macro-partial products. A model of the process of neuro-like encryption of control commands using a table-algorithmic method has been developed. Models for testing and debugging blocks of encryption (decryption), encoding (decoding), and masking (unmasking) of data have been developed, which, due to the use of reference values for comparison, ensure an increase in the quality of testing and debugging of the cryptographic system. A cryptographic system was developed, which, as a result of a dynamic change in the type of neuro-like network architecture and the values of weighting coefficients, mask codes and barker-like code, provides an increase in the crypto-resistance of data transmission. Testing of the simulation model was carried out on the example of message transmission for various configurations of a cryptographic system.
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