This article discusses the results of solving the problems of complex objects (CO) recovery programs, which are based on the structure dynamics management and control of these objects. The main advantage is the combined use of different models, methods and algorithms (analytical, simulation, logical-algebraic and their combinations) which allows to compensate their objectively existing shortcomings and limitations while enhancing their positive qualities during planning and scheduling for CO proactive intellectual situational management and control in emergencies. Proposed integration of CO management and control methods allows to link at the constructive level the substantive and formal aspects of the solving problem. Within the framework of the presented methodology, it is possible to rely on the fundamental scientific results obtained to date in the modern control theory of complex dynamic systems and knowledge engineering with a tunable structure during the situational management of complex objects recovery. It allows to determine the sequence of tasks and operations (to synthesize CO disaster recovery plans and schedules), to find and reasonably choose compromise solutions in the presence of several options for the sequence of operations. The developed CO disaster recovery plans and schedules are evaluated by involving experts and identifying their implicit expertise with the help of multicriteria approach. The problem statement of recovery is given. The new method of multicriteria evaluation of the CO disaster recovery plans and schedules, based on a combination of theory of experiments design models and models of fuzzy rule-based language is given. © 2020, Springer Nature Switzerland AG.

Attribute-Based Access Control (ABAC) model is a perspective access control model for cloud infrastructures used for automation of industrial, transport and energy systems as they include large number of users, resources and dynamical changed permissions. The paper considers the features of ABAC model and the theoretical background for verification of the ABAC policies based on the model checking. The possibility of applying the model checking is justified on the example of the ABAC policy. Implementation of the proposed approach was made using the UPPAAL verification tool. Experimental assessment shows high acceptability of the model checking not only for finding anomalies in ABAC policies but for finding decisions to eliminate them. © 2020, Springer Nature Switzerland AG.

In this paper according to complex modeling approach and applying cyber-physical systems is proposed to use control theoretic description of supply chain. Cyber-physical systems are automatic control systems, which used to combine various objects by means of multichannel measuring systems with embedded software in various types of hierarchical structures. We modify multiple-model description of the supply chain by adding the dynamic model of measuring and computing operations control. The extended model allow us to describe the process of receiving the necessary information about the current state of the system. Cyber-physical systems have been applied and the classical methods of optimal program and position control have been transferred and modified for supply chain management (management of organizational and technological systems). © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

The analysis of the assessment methods of modern supply chain networks' (SCN) resilience while managing their configuration and reconfiguration under the conditions of predictable disruptions has shown that under the conditions of unpredictable disruptions these methods are not acceptable. In addition, these are not acceptable in case of the design and creation of SCNs, which are completely different in composition and structure from the known SCNs. This situation requires the development of conceptually new methodological foundations for assessing the SCN's resilience and analyzing such an important characteristic of SCN as structural resilience's configuration. The article presents possible ways of assessing the SCN's configurations of structural resilience, which depict the implementation of their own functions by elements and key nodes of the SCN as well as their participation in the production and technological processes of supply chain management. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

The paper is devoted to issues of the network traffic analysis in conditions of uncertain network protocol specifications. We propose an approach to identify typical structures of network protocols and determine their lexical specifications based on text-inspired methods for the structural analysis of raw data. High heterogeneity, partial lexical uncertainty and use of new, proprietary or modified data transfer protocols in computer networks explain high relevance of the research topic. We present the technique of network traffic analysis and the results of experiments, that confirm the applicability of the proposed approach. © 2019 IEEE.

The use of the virtual local area networks (VLAN) technology is a well-known method of restricting access to network elements in heterogeneous network infrastructures, including critical infrastructures. The essence of the VLAN usage is to create a set of virtual subnets and in the distribution of computers on these subnets. This distribution is described by a "computer-subnet" matrix, called the VLAN-based access control scheme. The formation of an access control scheme is an NP-complete problem, and for its solution several methods are known, including genetic algorithms. However, for large critical infrastructures, the solution of this problem by known methods is very laborious due to its large dimension. The paper proposes to introduce the concept of "roles" for VLANs and use the role-based approach to optimize VLAN-based access control schemes. To solve the optimization problem, an improved genetic algorithm is proposed. Improvements are associated with the multi-chromosome representation of individuals, a new type of fitness function, a two-dimensional type of crossover operation, and a number of other aspects. The results of the experiments show the high efficiency of the proposed genetic algorithm. © 2019 Association for Computing Machinery.

The design of multidimensional velocity, position and force control algorithms for a semi-automatic motion control system of a robot-manipulator has been performed. Mathematical and computer models of a motion control system with reconfigurable structure have been developed for a 3-link robot performing standard operations set by a human operator with a 3-degree-of-freedom handle. Simulation of dynamic processes in a system with different control algorithms has been performed and their precision characteristics have been evaluated. The achieved results may be of interest for designers who develop training simulators for human supervisors of robot motion control systems. ©ECMS Mauro Iacono, Francesco Palmieri, Marco Gribaudo, Massimo Ficco (Editors).

The paper proposes an approach for visualization of access control systems based on triangular matrices. The approach is used for visualization of access control security model that based in methods of RBAC and Take-Grant. In comparison with regular access matrices, the sparseness of triangular matrices is less, and the approach is able to visualize nesting at the level of rights. The paper outlines a new triangular visualization model, its interpretation, management methods, and the results of experiments for visualization of an access control system in an IT company. © 2019 IEEE.

The article describes the approach to designing proactive decision support systems (DSS) based on the modification of the generalized computational model as a knowledge representation model (KRM). It is proposed to use a precedent methodology for making management decisions. It was found that this approach allows to predict the situations and ensure the model’s self-learning by forming a precedent knowledge base. © 2019, Springer International Publishing AG, part of Springer Nature.

Image segmentation is the process of subdividing an image into regions that are consistent and homogeneous in some characteristics. An important factor in the recognition of magnetic resonance images is not only the accuracy, but also the speed of the segmentation procedure. Modified Exponential Particle Swarm Optimization algorithm is proposed in paper. The time complexity of proposed algorithm is investigated using consequences from Drift theorem. It is established that the proposed algorithm has a polynomial estimation of complexity. Images from the Ossirix image dataset and real medical images were used for testing. © Springer Nature Switzerland AG 2019.