SYNERGY OF BUILDING CYBERSECURITY SYSTEMS

The development of the modern world community is closely related to advances in computing resources and cyberspace. The formation and expansion of the range of services is based on the achievements of mankind in the field of high technologies. However, the rapid growth of computing resources, the emergence of a full-scale quantum computer tightens the requirements for security systems not only for information and communication systems, but also for cyber-physical systems and technologies. The methodological foundations of building security systems for critical infrastructure facilities based on modeling the processes of behavior of antagonistic agents in security systems are discussed in the first chapter. The concept of information security in social networks, based on mathematical models of data protection, taking into account the influence of specific parameters of the social network, the effects on the network are proposed in second chapter. The nonlinear relationships of the parameters of the defense system, attacks, social networks, as well as the influence of individual characteristics of users and the nature of the relationships between them, takes into account. In the third section, practical aspects of the methodology for constructing post-quantum algorithms for asymmetric McEliece and Niederreiter cryptosystems on algebraic codes (elliptic and modified elliptic codes), their mathematical models and practical algorithms are considered. Hybrid crypto-code constructions of McEliece and Niederreiter on defective codes are proposed. They can significantly reduce the energy costs for implementation, while ensuring the required level of cryptographic strength of the system as a whole. The concept of security of corporate information and educational systems based on the construction of an adaptive information security system is proposed. ISBN 978-617-7319-31-2 (on-line)ISBN 978-617-7319-32-9 (print) ------------------------------------------------------------------------------------------------------------------ How to Cite: Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O., Korol, O., Milevskyi, S. et. al.; Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O. (Eds.) (2021). Synergy of building cybersecurity systems. Kharkiv: РС ТЕСHNOLOGY СЕNTЕR, 188. doi: http://doi.org/10.15587/978-617-7319-31-2 ------------------------------------------------------------------------------------------------------------------ Indexing:                    Розвиток сучасної світової спільноти тісно пов’язаний з досягненнями в області обчислювальних ресурсів і кіберпростору. Формування та розширення асортименту послуг базується на досягненнях людства у галузі високих технологій. Однак стрімке зростання обчислювальних ресурсів, поява повномасштабного квантового комп’ютера посилює вимоги до систем безпеки не тільки інформаційно-комунікаційних, але і до кіберфізичних систем і технологій. У першому розділі обговорюються методологічні основи побудови систем безпеки для об'єктів критичної інфраструктури на основі моделювання процесів поведінки антагоністичних агентів у систем безпеки. У другому розділі пропонується концепція інформаційної безпеки в соціальних мережах, яка заснована на математичних моделях захисту даних, з урахуванням впливу конкретних параметрів соціальної мережі та наслідків для неї. Враховуються нелінійні взаємозв'язки параметрів системи захисту, атак, соціальних мереж, а також вплив індивідуальних характеристик користувачів і характеру взаємовідносин між ними. У третьому розділі розглядаються практичні аспекти методології побудови постквантових алгоритмів для асиметричних криптосистем Мак-Еліса та Нідеррейтера на алгебраїчних кодах (еліптичних та модифікованих еліптичних кодах), їх математичні моделі та практичні алгоритми. Запропоновано гібридні конструкції криптокоду Мак-Еліса та Нідеррейтера на дефектних кодах. Вони дозволяють істотно знизити енергетичні витрати на реалізацію, забезпечуючи при цьому необхідний рівень криптографічної стійкості системи в цілому. Запропоновано концепцію безпеки корпоративних інформаційних та освітніх систем, які засновані на побудові адаптивної системи захисту інформації. ISBN 978-617-7319-31-2 (on-line)ISBN 978-617-7319-32-9 (print) ------------------------------------------------------------------------------------------------------------------ Як цитувати: Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O., Korol, O., Milevskyi, S. et. al.; Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O. (Eds.) (2021). Synergy of building cybersecurity systems. Kharkiv: РС ТЕСHNOLOGY СЕNTЕR, 188. doi: http://doi.org/10.15587/978-617-7319-31-2 ------------------------------------------------------------------------------------------------------------------ Індексація:                 &nbsp

Integrated intelligent systems for industrial automation: the challenges of Industry 4.0, information granulation and understanding agents .

The objective of the paper consists in considering the challenges of new automation paradigm Industry 4.0 and reviewing the-state-of-the-art in the field of its enabling information and communication technologies, including Cyberphysical Systems, Cloud Computing, Internet of Things and Big Data. Some ways of multi-dimensional, multi-faceted industrial Big Data representation and analysis are suggested. The fundamentals of Big Data processing with using Granular Computing techniques have been developed. The problem of constructing special cognitive tools to build artificial understanding agents for Integrated Intelligent Enterprises has been faced

Techniques for automated parameter estimation in computational models of probabilistic systems

The main contribution of this dissertation is the design of two new algorithms for automatically synthesizing values of numerical parameters of computational models of complex stochastic systems such that the resultant model meets user-specified behavioral specifications. These algorithms are designed to operate on probabilistic systems – systems that, in general, behave differently under identical conditions. The algorithms work using an approach that combines formal verification and mathematical optimization to explore a model\u27s parameter space. The problem of determining whether a model instantiated with a given set of parameter values satisfies the desired specification is first defined using formal verification terminology, and then reformulated in terms of statistical hypothesis testing. Parameter space exploration involves determining the outcome of the hypothesis testing query for each parameter point and is guided using simulated annealing. The first algorithm uses the sequential probability ratio test (SPRT) to solve the hypothesis testing problems, whereas the second algorithm uses an approach based on Bayesian statistical model checking (BSMC). The SPRT-based parameter synthesis algorithm was used to validate that a given model of glucose-insulin metabolism has the capability of representing diabetic behavior by synthesizing values of three parameters that ensure that the glucose-insulin subsystem spends at least 20 minutes in a diabetic scenario. The BSMC-based algorithm was used to discover the values of parameters in a physiological model of the acute inflammatory response that guarantee a set of desired clinical outcomes. These two applications demonstrate how our algorithms use formal verification, statistical hypothesis testing and mathematical optimization to automatically synthesize parameters of complex probabilistic models in order to meet user-specified behavioral propertie

Foundations of Cryptoeconomic Systems

Blockchain networks and similar cryptoeconomic networks aresystems, specifically complex systems. They are adaptive networkswith multi-scale spatiotemporal dynamics. Individual actions towards a collective goal are incentivized with "purpose-driven" tokens. These tokens are equipped with cryptoeconomic mechanisms allowing a decentralized network to simultaneously maintain a universal state layer, support peer-to-peer settlement, andincentivize collective action. These networks therefore provide a mission-critical and safety-critical regulatory infrastructure for autonomous agents in untrusted economic networks. They also provide a rich, real-time data set reflecting all economic activities in their systems. Advances in data science and network sciencecan thus be leveraged to design and analyze these economic systems in a manner consistent with the best practices of modern systems engineering. Research that reflects all aspects of these socioeconomic networks needs (i) a complex systems approach, (ii) interdisciplinary research, and (iii) a combination of economic and engineering methods, here referred to as "economic systems engineering", for the regulation and control of these socio-economicsystems. This manuscript provides foundations for further research activities that build on these assumptions, including specific research questions and methodologies for future research in this field.Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc

Real-time robotic tasks for cyber-physical avatars

Although modern robots can perform complex tasks using sophisticated algorithms that are specialized to a particular task and environment, creating robots capable of completing tasks in unstructured environments without human guidance (e.g., through teleoperation) remains a challenge. In this research, we present a framework to meet this challenge for a "cyberphysical avatar," which is defined to be a semi-autonomous robotic system that adjusts to an unstructured environment and performs physical tasks subject to critical timing constraints while under human supervision. This thesis first realizes a cyberphysical avatar that integrates three key technologies: (1) whole body-compliant control, (2) skill acquisition from machine learning (neuroevolution methods and deep learning), and (3) vision-based control through visual servoing. Body-compliant control is essential for operator safety because avatars perform cooperative tasks in close proximity to humans; machine learning enables "programming" avatars such that they can be used by non-experts for a large array of tasks, some unforeseen, in an unstructured environment; the visual servoing technique is indispensable for facilitating feedback control in human avatar interaction. This thesis proposes and demonstrates a systematically incremental approach to automating robotic tasks by decomposing a non-trivial task into stages, each of which may be automated by integrating the aforementioned techniques. We design and implement the controllers for two semi-autonomous robots that integrate three key techniques for grasping and pick-and-place tasks. While a general theory is beyond reach, we present a study on the tradeoffs between three design metrics for robotic task systems: (1) the amount of training effort for the robots to perform the task, (2) the time available to complete the task when the command is given, and (3) the quality of the result of the performed task. The tradeoff study in this design space uses the imprecise computation model as a framework to evaluate specific types of tasks: (1) grasping an unknown object and (2) placing the object in a target position. We demonstrate the generality of our integration methodology by applying it to two different robots, Dreamer and Hoppy. Our approach is evaluated by the performance of the robots in trading off between task completion time, training time and task completion success rate, in an environment similar to those in the recent Amazon Picking Challenge.Computer Science

Принципы создания прототипа цифрового двойника процесса алкилирования бензола пропиленом на основе нейронной сети

Objectives. To identify the principles of creating digital twins of an operating technological unit along the example of the process of liquid-phase alkylation of benzene with propylene, and to establish the sequence of stages of formation of a digital twin, which can be applied to optimize oil and gas chemical production.Methods. The chemical and technological system consisting of reactor, mixer, heat exchangers, separator, rectification columns, and pump is considered as a complex high-level system. Data was acquired in order to describe the functioning of the isopropylbenzene production unit. The main parameters of the process were calculated by simulation modeling using UniSim® Design software. A neural network model was developed and trained. The influence of various factors of the reaction process of alkylation, separation of reaction products, and evaluation of economic factors providing market interest of the industrial process was also considered. The adequacy of calculations was determined by statistics methods. A microcontroller prototype of the process was created.Results. A predictive neural network model and its creation algorithm for the process of benzene alkylation was developed. This model can be loaded into a microcontroller to allow for real-time determination of the economic efficiency of plant operation and automated optimization depending on the following factors: composition of incoming raw materials; the technological mode of the plant; the temperature mode of the process; and the pressure in the reactor.Conclusions. The model of a complex chemicotechnological system of cumene production, created and calibrated on the basis of long-term industrial data and the results of calculations of the output parameters, enables the parameters of the technological process of alkylation to be calculated (yield of reaction products, energy costs, conditional profit at the output of finished products). During the development of a hardware-software prototype, adapted to the operation of the real plant, the principles and stages of creating a digital twin of the operating systems of chemical technology industries were identified and formulated.Цели. Выявление принципов создания цифровых двойников реально действующей технологической установки на примере процесса жидкофазного алкилирования бензола пропиленом и установление последовательности этапов формирования цифрового двойника, которая может быть применима для оптимизации работы нефтегазохимического производства.Методы. Рассмотрена в целом химико-технологическая система, состоящая из реактора, смесителя, теплообменников, сепаратора, ректификационных колонн и насоса, как система высокого уровня. Выполнен сбор данных, описывающих функционирование установки получения изопропилбензола алкилированием бензола пропиленом путем расчета основных параметров процесса с помощью имитационного моделирования с применением специализированного программного обеспечения UniSim® Design. Разработана и обучена нейросетевая модель, учитывающая влияние различных факторов реакционного процесса алкилирования, разделения продуктов реакции и оценки экономических факторов, обеспечивающих рыночную привлекательность рассматриваемого промышленного процесса. Определена адекватность результатов расчетов оптимальных параметров процесса методами математической статистики. Создан прототип цифрового двойника процесса, реализованной на микроконтроллере.Результаты. Создана прогностическая нейросетевая модель и алгоритм ее построения для процесса алкилирования бензола пропиленом, позволяющая при загрузке ее в микроконтроллер обеспечить в режиме реального времени определение экономической эффективности работы установки и автоматическую оптимизацию работы установки в зависимости от состава поступающего сырья технологического режима системы, температурного режима проведения процесса и давления в реакторе.Выводы. Созданная модель сложной химико-технологической системы производства кумола, откалиброванная на основании промышленных данных длительного пробега технологической установки и результатов расчетов выходных параметров процесса при помощи нейронной сети, реализованной на микроконтроллере, позволяет рассчитать параметры технологического процесса алкилирования (выход продуктов реакции, энергетические затраты, условную прибыль при выпуске готовой продукции). В процессе разработки прототипа программно-аппаратного комплекса управления установкой алкилирования бензола пропиленом на основе данных, адаптированных к работе реальной установки, были выявлены и сформулированы принципы и этапы создания цифрового двойника производственных систем отраслей химической технологии