scholarly journals Cybersecurity Risk Assessment in Smart City Infrastructures

Machines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 78
Author(s):  
Maxim Kalinin ◽  
Vasiliy Krundyshev ◽  
Peter Zegzhda
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Smart City ◽  
Urban Infrastructure ◽  
Quantitative Risk Assessment ◽  
Main Concern ◽  
Security Threats ◽  
New Approach ◽  
Security Indicators ◽  
Cyber Risk

The article is devoted to cybersecurity risk assessment of the dynamic device-to-device networks of a smart city. Analysis of the modern security threats at the IoT/IIoT, VANET, and WSN inter-device infrastructures demonstrates that the main concern is a set of network security threats targeted at the functional sustainability of smart urban infrastructure, the most common use case of smart networks. As a result of our study, systematization of the existing cybersecurity risk assessment methods has been provided. Expert-based risk assessment and active human participation cannot be provided for the huge, complex, and permanently changing digital environment of the smart city. The methods of scenario analysis and functional analysis are specific to industrial risk management and are hardly adaptable to solving cybersecurity tasks. The statistical risk evaluation methods force us to collect statistical data for the calculation of the security indicators for the self-organizing networks, and the accuracy of this method depends on the number of calculating iterations. In our work, we have proposed a new approach for cybersecurity risk management based on object typing, data mining, and quantitative risk assessment for the smart city infrastructure. The experimental study has shown us that the artificial neural network allows us to automatically, unambiguously, and reasonably assess the cyber risk for various object types in the dynamic digital infrastructures of the smart city.

scholarly journals Approaches to the assessment the innovation-and-investment projects within the system of “Smart City” criteria

2019 ◽  
Vol 97 ◽  
pp. 01022
Author(s):  
Tatyana Miroshnikova ◽  
Natalia Taskaeva
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Life Cycle ◽  
Smart City ◽  
Quantitative Risk Assessment ◽  
Modern Approach ◽  
Investment Projects ◽  
Construction Companies ◽  
Construction Organizations ◽  
The Impact

The article clarifies the understanding of modern approaches to risk management in construction organizations. The authors have formed a classification of the sources of risks in construction and the reasons causing the uncertainty of the conditions of operation of construction companies. The researchers identified factors that require control in the construction industry. The authors offer, that “smart city” assumes six criteria, including smart economy, smart mobility, smart environment, smart people, smart living, smart governance. The consideration of the tendency to innovations and the assessment of innovation-and-investment risks within the concept “Smart city” was carried out for the Russian practice for the first time. The risk assessment is offered to be carried out with the use of the modern approach. The proposed approach to improve risk management, according to which all the basic processes of risk management should be carried out at each stage of the life cycle of a construction object. The authors propose to use certain methods of qualitative and quantitative risk assessment, enshrined in the risk management standard, at the appropriate stages of the life cycle of a construction object in terms of their advantages. This will increase the effectiveness of risk management and minimize the impact of risk factors identified by researchers on the performance of construction organizations. Research of risk management systems allowed us to determine the priorities and problems of construction companies in the field of risk management and increase its efficiency.

scholarly journals Epistemological Equation for Analysing Uncontrollable States in Complex Systems: Quantifying Cyber Risks from the Internet of Things

2021 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Pete Burnap ◽  
Omar Santos
Keyword(s):  
Risk Assessment ◽  
Internet Of Things ◽  
Empirical Analysis ◽  
Quantitative Risk Assessment ◽  
The Internet ◽  
Self Assessment ◽  
Target State ◽  
Epistemological Analysis ◽  
Cyber Risk ◽  
The Internet Of Things

AbstractThe Internet-of-Things (IoT) triggers data protection questions and new types of cyber risks. Cyber risk regulations for the IoT, however, are still in their infancy. This is concerning, because companies integrating IoT devices and services need to perform a self-assessment of its IoT cyber security posture. At present, there are no self-assessment methods for quantifying IoT cyber risk posture. It is considered that IoT represent a complex system with too many uncontrollable risk states for quantitative risk assessment. To enable quantitative risk assessment of uncontrollable risk states in complex and coupled IoT systems, a new epistemological equation is designed and tested though comparative and empirical analysis. The comparative analysis is conducted on national digital strategies, followed by an empirical analysis of cyber risk assessment approaches. The results from the analysis present the current and a target state for IoT systems, followed by a transformation roadmap, describing how IoT systems can achieve the target state with a new epistemological analysis model. The new epistemological analysis approach enables the assessment of uncontrollable risk states in complex IoT systems—which begin to resemble artificial intelligence—and can be used for a quantitative self-assessment of IoT cyber risk posture.

Fuzzy Rules for Risk Assessment and Contingency Estimation within COCOMO Software Project Planning Model

2014 ◽  
pp. 88-111 ◽  
Author(s):  
Ekananta Manalif ◽  
Luiz Fernando Capretz ◽  
Danny Ho
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Project Planning ◽  
Project Managers ◽  
Research Data ◽  
Software Project ◽  
Planning Model ◽  
Effort Estimation ◽  
New Approach ◽  
Project Risks

Software development can be considered to be the most uncertain project when compared to other projects due to uncertainty in the customer requirements, the complexity of the process, and the intangible nature of the product. In order to increase the chance of success in managing a software project, the project manager(s) must invest more time and effort in the project planning phase, which involves such primary and integrated activities as effort estimation and risk management, because the accuracy of the effort estimation is highly dependent on the size and number of project risks in a particular software project. However, as is common practice, these two activities are often disconnected from each other and project managers have come to consider such steps to be unreliable due to their lack of accuracy. This chapter introduces the Fuzzy-ExCOM Model, which is used for software project planning and is based on fuzzy technique. It has the capability to not only integrate the effort estimation and risk assessment activities but also to provide information about the estimated effort, the project risks, and the effort contingency allowance necessary to accommodate the identified risk. A validation of this model using the project’s research data shows that this new approach is capable of improving the existing COCOMO estimation performance.

Fuzzy Rules for Risk Assessment and Contingency Estimation Within COCOMO Software Project Planning Model

2018 ◽  
pp. 771-797
Author(s):  
Ekananta Manalif ◽  
Luiz Fernando Capretz ◽  
Danny Ho
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Project Planning ◽  
Project Managers ◽  
Research Data ◽  
Software Project ◽  
Planning Model ◽  
Effort Estimation ◽  
New Approach ◽  
Project Risks

Software development can be considered to be the most uncertain project when compared to other projects due to uncertainty in the customer requirements, the complexity of the process, and the intangible nature of the product. In order to increase the chance of success in managing a software project, the project manager(s) must invest more time and effort in the project planning phase, which involves such primary and integrated activities as effort estimation and risk management, because the accuracy of the effort estimation is highly dependent on the size and number of project risks in a particular software project. However, as is common practice, these two activities are often disconnected from each other and project managers have come to consider such steps to be unreliable due to their lack of accuracy. This chapter introduces the Fuzzy-ExCOM Model, which is used for software project planning and is based on fuzzy technique. It has the capability to not only integrate the effort estimation and risk assessment activities but also to provide information about the estimated effort, the project risks, and the effort contingency allowance necessary to accommodate the identified risk. A validation of this model using the project's research data shows that this new approach is capable of improving the existing COCOMO estimation performance.

scholarly journals Integrated challenge test: a new approach evaluating quantitative risk assessment of Listeria in ready to eat foods

2013 ◽  
Vol 1 (6) ◽  
pp. 20
Author(s):  
Stefano Colombo ◽  
Marco Romani ◽  
Chiara Romani ◽  
Paolo Matteini
Keyword(s):  
Risk Assessment ◽  
Challenge Test ◽  
Quantitative Risk Assessment ◽  
New Approach

scholarly journals Banking activity. Management by risk assessment and measurement

2009 ◽  
Author(s):  
Vasile Gotcu
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Financial Markets ◽  
New Products ◽  
Financial Flows ◽  
New Approach ◽  
Banking Activity ◽  
Activity Management ◽  
The Stability

Rapid innovations in financial markets and the internationalization of the financial flows have created opportunities for developing some new products and supplying a wider product and service range to the banks. Liberalization of the financial markets , the severe competition and the diversification of the offered products expose banks to new risks and provocations. This new approach confirms the fact that the banking management generally and the risk management especially represents essential concern for the security and the stability both of each bank and the entire banking<br />system.

Implementation of Quantitative Risk Assessment: Case Study

2014 ◽  
Author(s):  
David Mangold ◽  
W. Kent Muhlbauer ◽  
Jim Ponder ◽  
Tony Alfano
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Risk Management ◽  
The United States ◽  
Management Program ◽  
Quantitative Risk Assessment ◽  
Management Decision ◽  
Classical Statistics ◽  
Wide Range

Risk management of pipelines is a complex challenge due to the dynamic environment of the real world coupled with a wide range of system types installed over many decades. Various methods of risk assessment are currently being used in industry, many of which utilize relative scoring. These assessments are often not designed for the new integrity management program (IMP) requirements and are under direct challenge by regulators. SemGroup had historically used relative risk assessment methodologies to help support risk management decision-making. While the formality offered by these early methods provided benefits, it was recognized that, in order to more effectively manage risk and better meet the United States IMP objectives, a more effective risk assessment would be needed. A rapid and inexpensive migration into a better risk assessment platform was sought. The platform needed to be applicable not only to pipeline miles, but also to station facilities and all related components. The risk results had to be readily understandable and scalable, capturing risks from ‘trap to trap’ in addition to risks accompanying each segment. The solution appeared in the form a quantitative risk assessment that was ‘physics based’ rather than the classical statistics based QRA. This paper will outline the steps involved in this transition process and show how quantitative risk assessment may be efficiently implemented to better guide integrity decision-making, illustrated with a case study from SemGroup.

Industry Process Safety

2020 ◽  
pp. 117-151
Author(s):  
Ales Bernatik
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Technical Progress ◽  
Accident Prevention ◽  
Quantitative Risk Assessment ◽  
Process Safety ◽  
Industrial Accidents ◽  
New Approaches ◽  
Industrial Companies ◽  
Major Accident

This chapter deals with the issue of process safety in industrial companies and major accident prevention. In the present-day technologically advanced world, industrial accidents appear ever more frequently, and the field of major accident prevention has become a dynamically developing discipline. With accelerating technical progress, risks of industrial accidents are to be reduced. In the first part, possible approaches to quantitative risk assessment are presented; and continuing it focuses on the system of risk management in industrial establishments. This chapter aims at providing experiences, knowledge, as well as new approaches to the prevention of major accidents caused by the implementation of the Seveso III Directive.

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