Assessing and managing risks in smart computing applications
-
Sanjive Saxena
Abstract
Smart computing applications have invaded our lives profoundly. As a result, these applications have become ubiquitous. Further, as we continue to fiddle with our smart device showing these smart applications, there is always an imminent danger lurking around with the growing usage of this combination. The danger lies in the form of risks associated with the exponential growth of consumption of these smart applications, devices, and Internet. However, risks are somewhat unwanted components that are likely to generate a negative impact in the future, thus impeding our work and unleashing destruction in one form or the other, if and when it occurs. Hence, it needs to be managed. In other words, it must be planned, assessed, and consequently, mitigation plans be developed to minimize the impact when it occurs. This chapter deals with the issues of risk assessment and risk management in the context of smart computing applications. The design of the chapter follows a structured approach. Commencing with the process of identification of vital assets and the risks associated with these assets, the chapter then moves to the processes responsible for assessing and managing these risks. The backbone of the chapter is based on two standard models: ISO 27001 and ISO 31000. While ISO 27001 deals with information security management, ISO 31000 deals with risk management. In today’s highly competitive and complex world, the application of knowledge has brought a significant transformation in terms of value addition, growth of the business, and the development of new products and services. This apparent shift toward knowledge engineering, knowledge management, and its application in providing a competitive edge has opened a new arena of information security and risks associated with the mismanagement of information and the consequent impact on business operations. This chapter deals with these aspects. Finally, as an appendix, the chapter covers a practical application of risk assessment and its management in smart computing applications.
Abstract
Smart computing applications have invaded our lives profoundly. As a result, these applications have become ubiquitous. Further, as we continue to fiddle with our smart device showing these smart applications, there is always an imminent danger lurking around with the growing usage of this combination. The danger lies in the form of risks associated with the exponential growth of consumption of these smart applications, devices, and Internet. However, risks are somewhat unwanted components that are likely to generate a negative impact in the future, thus impeding our work and unleashing destruction in one form or the other, if and when it occurs. Hence, it needs to be managed. In other words, it must be planned, assessed, and consequently, mitigation plans be developed to minimize the impact when it occurs. This chapter deals with the issues of risk assessment and risk management in the context of smart computing applications. The design of the chapter follows a structured approach. Commencing with the process of identification of vital assets and the risks associated with these assets, the chapter then moves to the processes responsible for assessing and managing these risks. The backbone of the chapter is based on two standard models: ISO 27001 and ISO 31000. While ISO 27001 deals with information security management, ISO 31000 deals with risk management. In today’s highly competitive and complex world, the application of knowledge has brought a significant transformation in terms of value addition, growth of the business, and the development of new products and services. This apparent shift toward knowledge engineering, knowledge management, and its application in providing a competitive edge has opened a new arena of information security and risks associated with the mismanagement of information and the consequent impact on business operations. This chapter deals with these aspects. Finally, as an appendix, the chapter covers a practical application of risk assessment and its management in smart computing applications.
Chapters in this book
- Frontmatter I
- Contents V
- Knowledge engineering for industrial expert systems 1
- Machine learning integrated blockchain model for Industry 4.0 smart applications 13
- Prototyping the expectancy disconfirmation theory model for quality service delivery in federal university libraries in Nigeria 26
- Design of chatbot using natural language processing 60
- Algorithm development based on an integrated approach for identifying cause and effect relationships between different factors 80
- Risk analysis and management in projects 96
- Assessing and managing risks in smart computing applications 122
- COVID-19 visualization and exploratory data analysis 145
- Business intelligence and decision support systems: business applications in the modern information system era 156
- Business intelligence implementation in different organizational setup evidence from reviewed literatures 173
- Conceptualization of a modern digital-driven health-care management information system (HMIS) 187
- Knowledge engine for a Hindi text-to-scene generation system 201
- Index 229
Chapters in this book
- Frontmatter I
- Contents V
- Knowledge engineering for industrial expert systems 1
- Machine learning integrated blockchain model for Industry 4.0 smart applications 13
- Prototyping the expectancy disconfirmation theory model for quality service delivery in federal university libraries in Nigeria 26
- Design of chatbot using natural language processing 60
- Algorithm development based on an integrated approach for identifying cause and effect relationships between different factors 80
- Risk analysis and management in projects 96
- Assessing and managing risks in smart computing applications 122
- COVID-19 visualization and exploratory data analysis 145
- Business intelligence and decision support systems: business applications in the modern information system era 156
- Business intelligence implementation in different organizational setup evidence from reviewed literatures 173
- Conceptualization of a modern digital-driven health-care management information system (HMIS) 187
- Knowledge engine for a Hindi text-to-scene generation system 201
- Index 229
