The paper presents the results of the development of a method for assessing the security of cyber-physical systems based on the Lotka–Volterra model. Security models of cyber-physical systems are proposed: “predator–prey” taking into account the computing capabilities and focus of targeted cyberattacks, “predator–prey” taking into account the possible competition of attackers in relation to the “prey”, “predator–prey” taking into account the relationships between “prey species” and “predator species”, “predator–prey” taking into account the relationship between “prey species” and “predator species”. Based on the proposed approach, the coefficients of the Lotka–Volterra model α=0.39, β=0.32, γ=0.29, φ=0.27 were obtained, which take into account the synergy and hybridity of modern threats, funding for the formation and improvement of the protection system, and also allow determining the financial and computing capabilities of the attacker based on the identified threats. The proposed method for assessing the security of cyber-physical systems is based on the developed threat classifier, allows assessing the current security level and provides recommendations regarding the allocation of limited protection resources based on an expert assessment of known threats. This approach allows offline dynamic simulation, which makes it possible to timely determine attackers' capabilities and form preventive protection measures based on threat analysis. In the simulation, actual bases for assessing real threats and incidents in cyber-physical systems can be used, which allows an expert assessment of their impact on both individual security services and security components (cyber security, information security and security of information). The presented simulation results do not contradict the graphical results of the classical Lotka–Volterra model, which indicates the adequacy of the proposed approach for assessing the security of cyber-physical systems

One of the pressing areas that is developing in the field of information security is associated with the use of Honeypots (virtual decoys, online traps), and the selection of criteria for determining the most effective Honeypots and their further classification is an urgent task. The main products that implement virtual decoy technologies are presented. They are often used to study the behavior, approaches and methods that an unauthorized party uses to gain unauthorized access to information system resources. Online hooks can simulate any resource, but more often they look like real production servers and workstations. A number of fairly effective developments are known that are used to solve the problems of detecting attacks on information system resources, which are based on the apparatus of fuzzy sets. They showed the effectiveness of the appropriate mathematical apparatus, the use of which, for example, to formalize the approach to the formation of a set of reference values that will improve the process of determining the most effective Honeypots. For this purpose, many characteristics have been formed (installation and configuration process, usage and support process, data collection, logging level, simulation level, interaction level) that determine the properties of online traps. These characteristics became the basis for developing a method for the formation of standards of linguistic variables for further selection of the most effective Honeypots. The method is based on the formation of a Honeypots set, subsets of characteristics and identifier values of linguistic estimates of the Honeypot characteristics, a base and derived frequency matrix, as well as on the construction of fuzzy terms and reference fuzzy numbers with their visualization. This will allow classifying and selecting the most effective virtual baits in the future.

Context. This paper presents a method for solving the problem of product's quality assurance at the stage of the initial manufacture process design in accordance with the process-analytical technology for the design of modern certified manufacturing-QbD. The method uses the information technologies of multivariate statistical analysis (MSA) to evaluate the influence of time multivariate critical process parameters (CPPs) on the time product critical quality attributes (CQAs). Preparatory transformation of clusters of critical process (manufacture process) parameters into factors of product critical quality attributes was carried out. Objective. To disclose the method of multivariate statistical analysis for assessing the character and features of the influence of time multivariate critical process parameters on time multivariate critical quality attributes at the design stage of the manufacture process. Method. The method consistently uses: statistical procedures of exploratory multivariate data analysis; transformation the homogeneous observed values matrices of CPPs and product CQAs into data frame (table) with factorized data; construction the regression trees of multivariate CPPs with a multivariate responses (CQAs). The method is implemented the R language packages software. Results. Factorized time multivariate CPPs make it possible to use methods of multivariate statistical analysis for evaluating the influence of CPPs factors on the time multivariate CQAs. Conclusions. This method of statistical analysis, together with statistical multivariate canonical analysis, represents an up-to-date information technology for detailed estimation the influence of time multivariate CPPs objects and some CPPs components on CQAs.

Due to the widespread use of sensors and sensor networks in the tasks of territory coverage, the relevant criteria are maximizing coverage and minimizing energy consumption. At the same time, the compliance of the network with these criteria is an urgent problem in the modern technological world. A modification of the method for constructing energy-efficient sensor networks is proposed by introducing an additional criterion for minimizing the number of sensors and limiting the number of sensors used, which allows reducing the energy consumption of sensor networks by 19 %. In the resulting optimization problem, the optimality criteria are the functions of minimizing the area of uncovered territory, the value of energy consumption, and the number of sensors. The optimum solution is formed by pairs of values of the coverage radius and the level of intersection of the coverage areas, which provide maximum coverage while minimizing energy consumption and the number of sensors used. To solve the problem, the parameter convolution method and the genetic algorithm were used. In the case of dynamic sensors, the problem is to find such a trajectory of the sensor that provides the maximum flyby of the territory with a minimum length. A grid algorithm is proposed to find the necessary trajectory. The presented algorithm consists in dividing the territory into nodes and estimating the value of the covered territory by the sensor in this node. After the formation of estimates, the search for a Hamiltonian path was used. The case of a multiply connected territory with the possibility of turning it into a simply connected one is considered. A scheme for finding the parameters of energy-efficient coverage of the territory using static and dynamic sensors is proposed.

В даній статті проведено детальний аналіз симетричних шифрування. На основі проведеного аналізу розроблено програмне забезпечення з використанням алгоритмів шифрування DES та AES.