The paper presents and discusses a novel method of biometrie identification based on ECG data. The main idea of the study is to apply Deep Neural Networks (DNN) for human identification based on the raw ECG signal. To improve overall system accuracy various signal pre-processing and outlier detection techniques have been applied. Also, to make ECG identification approach more user friendly, three-finger measurement scheme has been proposed. All experiments have been made using self-collected Lviv Biometric Data Set.

The experience of cloud-based computing technologies use in the Smart City class design is analyzed. In the considerable part of applications in the Smart City class design informational technologies of cloud-based computing combined with such technologies as GRID, IoT, BigData, OLAP, GIS are used. At the same time complex solutions systematically considering peculiarities of defined technologies are practically non-existent. To introduce the Smart City concept it is necessary to realize completely the system approach considering peculiarities of existing IT infrastructure and appropriate services. In such a case interests of a wide range of motivated organizations, companies, firms and great number of town residents should be taken into account as far as distinction of informational resources access rights are concerned. Layer architecture of the Smart City class informational system for accumulation and processing of diverse data obtained from intelligent providers were analyzed by the authors during the research. Characteristics and realization of informational technologies on the basis of cloud-based computing used in Smart City designs were reviewed. In further investigations it is reasonable to model system operation and develop its prototype for individual water and heat cost accounting as well as operational mobile customer accounts for received services. It is also necessary to establish possibilities of functions increase and integration with other subsystems of “Smart City Ternopil” design portfolio.

Particularly vulnerable spot for violation of information security is a data network, since it is impossible to guarantee the data protection when transferring them through a public environment (Internet, telephone lines, radio). Therefore, the information transmitted on different networks, particularly in need of security and the main way of providing it, is using the cryptographic methods. However, recent research has shown that classical cryptography gives a cause to look for new prospects and it could be quantum cryptography. Among all possible quantum cryptography technologies, quantum secure direct communication (e.g. Ping-Pong protocol) does not use any cryptographic transformations, so there is no key distribution problem and eavesdropping can be detected during transfer, thereby improving information transmitting reliability. In this paper security amplification method for Ping-Pong protocol was proposed. This method uses generated ternary pseudorandom sequence and transformations in Galois field. Accordingly, this could increase the protocol asymptotical security and accelerate its work at least 3 times.

The main aim of the paper is to present the computer models, algorithms and programs which can be applied in real time control of an A-frame winch motion. This control algorithm has to stabilize load position and compensate the weaving. On the basis of the model of A-frame dynamics, the proper optimisation tasks are defined and solved. In each task the various crane and sea conditions are assumed. As a result of this process the optimal winch drive courses assuring load stabilization are defined. This approach allows the neural network to be defined and applied in real-time conditions.

A review of the control laws (models) of alternating current arc steelmaking furnaces’ (ASF) electric modes (EM) is carried out. A phase-symmetric three-component additive fuzzy model of electrode movement control signal formation is proposed. A synthesis of fuzzy inference systems based on the Sugeno model for the implementation of the proposed additive three-component fuzzy law of arc length control is performed. A structural computer Simulink model of the EM control system in a high-power arc steelmaking furnace of the DSP-200 type with an ARDM-T-12 arcs power regulator is created. Computer research into control dynamics indicators under the influence of deterministic perturbations and also integral indicators of energy efficiency when handling stationary random arc lengths fluctuations (corresponding to various technological stages of melting) are carried out. A comparative analysis of dynamics indicators, energy efficiency, and electromagnetic compatibility of the proposed fuzzy and known differential model of ASF arc lengths control is carried out. The implementation of the proposed fuzzy three-component additive control model in comparison with the existing deterministic differential one reduces the dispersion of voltages, currents, and arcs powers, reduces electrical losses in an arc furnace high-power network by 10–22% and increases the average arc power by 0.9–1.5%.

Today incident detection mechanisms, that define CERT / CSIRT effectiveness, based mostly on two principles - signature and heuristic. Their disadvantage is that they are focused on mathematical models, which require a lot of time to prepare statistics and so it decreases CERT/CSIRT efficiency. In this work, we have proposed approaches to ensure CERT / CSIRT high efficiency and its evaluation. To detect incidents we suggest using mathematical models based on expert's estimations. The proposed method allows solving the problem of incident detection and its identification based on expert judgments in fuzzy conditions. To estimate CERT / CSIRT effectiveness was introduce baselines. It enabled to determine CERT / CSIRT effectiveness during the necessary period. The report by the following parameters should be carried out regularly to get the full picture of their changes and identify the main trend.