The article investigates the model of the power social network, which, in contrast to classical approaches, allows to analyze the dynamic processes of interaction of individual agents within the network, in particular the dissemination of information about social impact. Expansion of social networks, connection of new nodes leads to an increase in the load on the system as a whole and negatively affects the protection of users, including their personal data. Traditionally, security parameters in social networks are studied using statistical methods and generalized mathematical dependencies and are fragmentary. The aim of the article is to develop a methodology for assessing the security parameters of personal data for networks with a degree distribution of connectivity of nodes based on the study of their topological features. The research is carried out on the basis of the classical Barabashi-Albert model using the principle of preferential connection, which puts the probability of making new connections depending on the number of existing connections of the node. A larger node means more opportunities to pick up new connections added to the network. The main security parameters are: the degree of the node, the average path length, the probability of joining new nodes, the clustering factor, the correlation between the degrees of neighboring nodes. It is shown that increasing the degree of the node and the length of the middle path has a negative effect on the protection of personal data, as it increases the likelihood of interception of information. Also, with increasing clustering factor, the flow of information increases, which leads to an increase in the load on the protection system and negatively affects the protection. Correlation between the degrees of neighboring nodes affects the redistribution of information flows and can, depending on the degree of nodes, both negatively and positively affect the protection. Modeling for networks of different scales is carried out and conclusions on expediency of application of a technique are made.

Intensive development of means of receiving and transmitting digital images creates the problem of processing huge amounts of video information flows. There is a wide range of tasks in which images are considered as a source of information on the basis of which it is necessary to make a decision. Important tasks to be solved by intelligent video surveillance systems are: identification of objects and determination of their trajectories; measuring the speed of objects; detection of alarming events in the tasks of object-territorial protection in real time. One of the main operations in intelligent video surveillance systems in image processing for further analysis is the selection of contours of images of objects, because the contour contains all the necessary information to recognize objects by their shape. This approach allows you to not consider the internal points of the image and, thus, significantly reduce the amount of information processed. This makes it possible to analyze images in real time. Contour analysis is a set of methods for selecting, describing and processing image contours that allows you to describe, store, compare and search for objects presented in the form of their external contours, as well as effectively solve the main problems of pattern recognition — transfer, rotate and zoom image of the object. In this case, the contour means a space-length gap, difference or abrupt change in brightness values. The purpose of the publication is to consider the algorithms for selecting the contours of images of objects in the problems of detecting alarming events by intelligent video surveillance systems. The problem of selection of contours of images of objects in problems of detection of disturbing events by intelligent systems of video surveillance is considered. In order to improve the basic characteristics of intelligent video surveillance systems, algorithms for contouring images of objects are proposed to ensure the detection of four types of alarming events: the appearance and presence of the object in the surveillance zone, moving the object in the forbidden direction, leaving the object and overturning the object.