In the Internet of Things, it is more important than ever to effectively address the problem of secure transmission based on steganographic substitution by synthesizing digital sensor data. In this case, the degree to which the grayscale message is obscured is a necessary issue. To ensure information security in IoT systems, various methods are used and information security problems are solved to one degree or another. The article proposes a method and algorithm for a computer image in grayscale, in which the value of each pixel is one sample, representing the amount of light, carrying only information about the intensity. The proposed method in grayscale using steganographic coding provides a secure implementation of data transmission in the IoT system. Study results were analyzed using PSNR (Peak Signal to Noise Ratio).

Today, the development of modern digital technologies requires them to solve existing cyber security problems. Thus, in this study, by building an algorithmic model for user access control based on a functional table, information security of existing systems can be used to create imitation of processes occurring in the system, which allows you to apply and analyze specific problems. This study attempted to focus on algorithmic issues.In this algorithmic model based on Functioning table, the user’s access control process is active at all transitions in the Petri net, and cases can be reached and detected with an initial marking, a sequence of transitions leading to a particular state.The algorithmic model based on the Functioning table of user access control has a strictly formal description that allows you to analyze the process of interaction of three subjects of information relations. This model allows switching the algorithmic model of user access control to the system to software implementation.

The main goal of steganography is to ensure secure communication while keeping the communicative act "invisible". The origin of this term dates back to Ancient Greece and translates as "hidden writing". A simple yet effective method of steganography in antiquity, considering the frequent use of wax tablets, involved cutting out the message on the wooden bottom of the tablet and then writing a decoy message on the wax. Technological evolution has led to human ingenuity, allowing the use of this powerful tool for both message transmission and watermarking products during the transition from physical to digital media. There are various forms of steganography, including injective, generative, substitutive, selective, and constructive. The steganography we employ is injective, as it is more suitable for our task of hiding information in image pixels. After various searches, we decided to use BMP (Bitmap Picture) 3 (Microsoft Windows NT) and later versions as the image file format, as this version, especially in 24-bit and 32-bit encodings, represents a single color component. Each byte allows for altering the least significant bits without changing the external appearance of the image.

The article discusses the logical method of object recognition and the construction of corrective functions. To construct a logical method for classifying objects, the method for constructing the optimal continuation of logical correcting functions is used. An algorithm for the optimal continuation of logical correcting functions is constructed and an estimate of the complexity of the constructed algorithm is calculated. A theorem is proved that the search algorithm for the minimum upper zero of a Boolean monotone function $\mu_{F}(y_{1},\ y_{2},\ \ldots,\ y_{n})$ is in one-to-one correspondence with the problem of finding a minimal set of variables that is essential for a function $F(x_{1},\ x_{2},\ \ldots,\ x_{n})$ that is not defined everywhere.