In this paper, the existing models of supply chain resilience assessment are extended by incorporating ripple effect and structure reconfiguration. Ripple effect mitigation control is vital for supply chain risk management from positions of structural resilience and recoverability. The research approach is based on a hybrid fuzzy-probabilistic approach. The genome method is applied with the objective of including the structural properties of supply chain design into resilience assessment. A supply chain design resilience index is developed, and its computation and application are demonstrated. The results suggest a method of comparing different supply chain designs regarding the resilience both to disruption propagation and with recovery consideration. It also allows the identification of groups of critical suppliers whose failure interrupts supply chain operation.

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.

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.

This study develops a resilience control model and computational algorithm for simultaneous structural-operational design of supply chain (SC) structural dynamics and recovery policy control. Our model integrates both structural recovery control in the SC as a whole and the corresponding functional recovery control at individual firms in the SC. Such a comprehensive combination is unique in literature and affords more realistic application to SC resilience control decisions. The focus of our study is to advance insights into feedback-driven understanding of resilience within open system control context. We construct a model that allows theorizing the notion of SC resilience within a disruption dynamics profile as a product of degradation and recovery control loops and examine the conditions for changes of disruption profile states. We show that the deviations from the resilient trajectory are associated with structural and performance degradation, and the recovery operations in structural adaptation yield the performance recovery. We contribute to existing works by comprehensively modelling structural dynamics and operational dynamics within an integrated feedback-driven framework to enable proactive SC resilience control. Our approach conceptualizes a new perspective as compared to the more common closed system view where SC resilience is treated from the performance equilibrium point of view. The proposed approach can help explain and improve the firms' operations in multiple ways. First, the combination of structural and functional dynamics can help revealing the latent supply-demand allocations which would be disrupted in case of particular changes in the SC design and suggest re-allocations of supply and demand Second, the model can be used to perform the dynamic analysis of SC disruption and recovery and to explain the reasons of SC performance degradation and restoration. This analysis can be further used to improve SC risk mitigation policies and recovery plans.

Abstract: This paper comprises the development and implementation of systems using the concept of Internet of Things. Due to the active development of industries using the concept of the Internet of Things, the information security problem is getting more and more important. To create a protected module of information-telecommunication system which implements the Internet of Things concept, it is important to take into account all its aspects. To determine relevant threats, it is necessary to use the detailed risk analysis according to existing standards. Then choosing protection measures, one must rely on identified relevant threats. Actual threats and necessary protective actions are determined in this paper for implementation of Smart House computer appliance module, in order to develop a protected part of Smart House, which is necessary for realization of room access control. We solved the following tasks in the work, namely, description of the Smart Home system; description of steps and security evaluation of Smart Home; implementation of hardware assembly and writing a code for the selected fragment of the system; safety evaluation of the selected fragment of Smart House and identification of actual threats; making recommendations to counter threats; software implementation of one of the most important threats and software implementation of protective measures for the selected threat. The key peculiarity of the work is an integrated approach to the design by the use of specific intruder models, analysis of the system’s assets and evaluation of their security. © 2019, Allerton Press, Inc.

The studies on supply chain (SC) disruption management frequently assume the existence of some negative scenarios and suggest ways to proactively protect and reactively recover the SC operations and performance if such scenarios occur. Though, there is a paucity of research on how to support methodologically the detection of realistic disruption scenarios, ideally of different risk aversion degrees. The contribution of our study lies in a conceptualization of a new methodical approach to the detection of disruption scenarios, ripple effect dispersal and recovery paths in supply chains on the basis of structural genomes. The objective is to integrate and expand the existing knowledge gained isolated in robustness analysis and recovery planning into a comprehensive framework for building a theory as well as for managerial purposes. The outcomes of this research constitute a useful decision-making support tool that allows detecting disruption scenarios at different risk-aversion levels based on the quantification of the structural robustness with the use of the genome method and observing the scope of disruption propagation, i.e., the ripple effect. The advantage of using a robustness computation by the genome method is that this allows detecting both the disruption scenarios of different severity, the ripple effect dispersal, and the corresponding recovery paths. Our results can be of value for decision-makers to compare different supply chain structural designs regarding the robustness and to identify disruption scenarios that interrupt the supply chain operations to different extents. The scenario detection can be further used for identifying optimal reconfiguration paths to deploy proactive contingency and reactive recovery policies. We show a correlation between the risk aversion degree of disruption scenarios and the outcomes of the reconfiguration policies.

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.

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.