Methodology for building secure artificial intelligence systems for electroretinography in ophthalmology

Abstract

Relevance. It is known that the method of electroretinography (hereinafter – ERG) in ophthalmology, which works on the key registration of changes in the bioelectric potential of the retina, uses the potential of exposure to light passing through the optical media of the eye. A similar method is conditionally applicable to the transmission of a light pulse over a fiber-optic cable, during which the correct transmission of information is carried out. If there is a violation or change in the electrical potential, there is every reason to believe that a person has any diseases. Purpose. To develop a technology for creating intellectual information security systems (IISS) is of a complex nature in which a quasi-biological paradigm is put in the first place, where the form of programming information processes, machine learning systems (MLS) and the construction of neural systems and ending with an AI architecture with built – in mechanisms for ensuring information security. Material and methods. In this article, a methodology for using a new artificial intelligence system (hereinafter referred to as AI) in a protected version for working with corrective devices for electroretinography in ophthalmology is compiled. Results. A set of methodological and scientific and technical solutions for the artificial intelligence system has been developed in order to ensure its «viability» and resistance to computer attacks aimed at violating the integrity. Conclusion. The article raises a key issue – the need to develop software architectural solutions for AI and adaptive neuro-fuzzy AI, which have «neurons» built into the software and hardware information protection systems with a universal set of commands for EG devices. Keywords: artificial intelligence, multi-agent system, electroretinography, neural network, integrity control, information security