scholarly journals A Conceptual Model for Internet of Things Risk Assessment in Healthcare Domain with Deep Learning Approach

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Mohd Nizam Zakaria ◽  
Nur Azaliah Abu Bakar ◽  
Hafiza Abas ◽  
Noor Hafizah Hassan
Keyword(s):  
Risk Assessment ◽  
Deep Learning ◽  
Internet Of Things ◽  
Risk Mitigation ◽  
Assessment Model ◽  
It Industry ◽  
Risk Assessment Models ◽  
Review Analysis ◽  
The Internet Of Things

The Internet of Things (IoT) has become a prevalent technology in the IT industry. One of the industries that can benefit extensively in this technology is healthcare. However, the healthcare IoT is still under debate with several studies suggesting it is lack of interoperability, security, and too much complexity. Even more, the risk involved in deploying it is still enormous. Many traditional risk assessment models are unable to provide a specific IoT risk guideline and specification, especially in the healthcare area. Thus, it is essential to understand the full extent of the IoT risk and how to manage its risk in the healthcare area. The risk management models, such as NIST SP 800-30, ISO/IEC 27005, OCTAVE, CRAMM, and EBIOS, which are among the leading and widely used in many areas and healthcare fields, have also been described. Besides, this paper includes a review of three IoT risk assessment models that are based on ABA-IDS, Deep Learning, and AHP-SVM. Based on the review analysis, we proposed a new enhanced healthcare IoT risk assessment model, which aims to provide a real-time monitoring and mitigating risks that incorporate the NIST SP 800-30 framework, ABA-IDS, and CNN deep learning. This shall constitute a better classification of each risk identified to find the best risk mitigation plan.

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.

scholarly journals Explosion risk assessment model for underground mine atmosphere

2016 ◽  
Vol 35 (1) ◽  
pp. 21-35 ◽  
Author(s):  
Jianwei Cheng ◽  
Xixi Zhang ◽  
Apurna Ghosh
Keyword(s):  
Risk Assessment ◽  
Risk Mitigation ◽  
Influence Factors ◽  
Safety Margin ◽  
Mining Industry ◽  
Critical Time ◽  
Underground Mine ◽  
Time Span ◽  
Assessment Model ◽  
Explosion Risk

In the coal mining industry, explosions or mine fires present the most hazardous safety threats for coal miners or mine rescue members. Hence, the determination of the mine atmosphere explosibility and its evolution are critical for the success of mine rescues or controlling the severity of a mine accident. However, although there are numbers of methods which can be used to identify the explosibility, none of them could well indicate the change to the explosion risk time evolution. The reason is that the underground sealed atmospheric compositions are so complicated and their dynamical changes are also affected by various influence factors. There is no one method that could well handle all such considerations. Therefore, accurately knowing the mine atmospheric status is still a complicated problem for mining engineers. Method of analyzing the explosion safety margin for an underground sealed atmosphere is urgently desired. This article is going to propose a series of theoretical explosion risk assessment models to fully analyze the evolution of explosion risk in an underground mine atmosphere. Models are based on characteristics of the Coward explosibility diagram with combining mathematical analyzing approaches to address following problems: (1) for an “not-explosive” atmosphere, judging the evolution of explosion risk and estimating the change-of-state time span from “not-explosive” to “explosive” and (2) for an “explosive” atmosphere, estimating the “critical” time span of moving out of explosive zone and stating the best risk mitigation strategy. Such research efforts could not only help mine operators understand the explosibility risk of a sealed mine atmosphere but also provide a useful tool to wisely control explosive atmosphere away from any dangers. In order to demonstrate research findings, case studies for derived models are shown and are also used to instruct readers how to apply them. The results provide useful information for effectively controlling an explosive underground sealed atmosphere.

Internet of Things Application for Intelligent Cities

2021 ◽  
pp. 251-270
Author(s):  
Wissam Abbass ◽  
Amine Baina ◽  
Mostafa Bellafkih
Keyword(s):  
Risk Assessment ◽  
Internet Of Things ◽  
Smart Cities ◽  
Security Risk ◽  
Privacy And Security ◽  
Security Risk Assessment ◽  
Key Aspects ◽  
Dynamic Services ◽  
The Internet Of Things

The rapid growth of the world's population is placing a huge strain on the existing infrastructures. As a quest for accommodating this growth, interest is turned to the internet of things (IoT). In fact, the IoT is significantly improving today's quality of life by innovating the provided services and enhancing communication and interaction. Furthermore, it has also empowered real-time decision making by introducing dynamic services for innovative traffic handling, energy-efficient infrastructure saving, and public safety ensuring. However, IoT applications for smart cities is still a major issue as it lacks assuring privacy and security within provided services. In this chapter, the authors pinpoint IoT's security risk assessment challenges and examine its critical influence on smart cities. Additionally, they highlight the key aspects characterizing a smart city which also represent the critical assets requiring security risk assessment. Moreover, they discuss the resulting issues and their related countermeasures.

Role of the Internet of Things and deep learning for the growth of healthcare technology

2021 ◽  
pp. 113-127
Author(s):  
Dinesh Bhatia ◽  
S. Bagyaraj ◽  
S. Arun Karthick ◽  
Animesh Mishra ◽  
Amit Malviya
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
The Internet ◽  
Healthcare Technology ◽  
The Internet Of Things

scholarly journals Potential Invasion Risk of Pet Traded Lizards, Snakes, Crocodiles, and Tuatara in the EU on the Basis of a Risk Assessment Model (RAM) and Aquatic Species Invasiveness Screening Kit (AS-ISK)

Diversity ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 164 ◽  
Author(s):  
Oldřich Kopecký ◽  
Anna Bílková ◽  
Veronika Hamatová ◽  
Dominika Kňazovická ◽  
Lucie Konrádová ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Common Species ◽  
Assessment Model ◽  
Thamnophis Sirtalis ◽  
Indigenous Species ◽  
The European Union ◽  
Risk Assessment Models ◽  
Species Invasiveness ◽  
Establishment Potential ◽  
Negative Impacts

Because biological invasions can cause many negative impacts, accurate predictions are necessary for implementing effective restrictions aimed at specific high-risk taxa. The pet trade in recent years became the most important pathway for the introduction of non-indigenous species of reptiles worldwide. Therefore, we decided to determine the most common species of lizards, snakes, and crocodiles traded as pets on the basis of market surveys in the Czech Republic, which is an export hub for ornamental animals in the European Union (EU). Subsequently, the establishment and invasion potential for the entire EU was determined for 308 species using proven risk assessment models (RAM, AS-ISK). Species with high establishment potential (determined by RAM) and at the same time with high potential to significantly harm native ecosystems (determined by AS-ISK) included the snakes Thamnophis sirtalis (Colubridae), Morelia spilota (Pythonidae) and also the lizards Tiliqua scincoides (Scincidae) and Intellagama lesueurii (Agamidae).

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