Threat Modelling and Risk Assessment in Internet of Things: A Review

2021 ◽  
pp. 293-305
Author(s):  
Mahapara Mahak ◽  
Yashwant Singh
Keyword(s):  
Risk Assessment ◽  
Internet Of Things ◽  
Threat Modelling

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 IoT(Internet of Things)-based Underground Risk Assessment System Surrounding Water Pipes in Korea

2015 ◽  
Vol 8 (11) ◽  
pp. 183-190 ◽  
Author(s):  
Pill-Jae Kwak ◽  
Sang-Hyuk Park ◽  
Chang-Ho Choi ◽  
Hyun-Dong Lee ◽  
Jae-Mo Kang ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Internet Of Things ◽  
Assessment System ◽  
Surrounding Water ◽  
Water Pipes

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.

IoT(Internet of Things)-based Underground Risk Assessment System Surrounding Water Pipes in Korea

2015 ◽  
Author(s):  
Pill-Jae Kwak ◽  
Sang-Hyuk Park ◽  
Chang-Ho Choi ◽  
Hyun-Dong Lee ◽  
Jae-Mo Kang ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Internet Of Things ◽  
Assessment System ◽  
Surrounding Water ◽  
Water Pipes

ANALYSIS OF PROTECTION PROTOCOLS AND RISK ASSESSMENT OF THEIR USE IN INTERNET NETWORKS

2021 ◽  
pp. 223-230
Author(s):  
Сергей Александрович Ермаков ◽  
Андрей Сергеевич Тулинов ◽  
Андрей Александрович Болгов ◽  
Валерий Константинович Власов
Keyword(s):  
Risk Assessment ◽  
Internet Of Things ◽  
Security Protocols ◽  
The Internet ◽  
Successful Implementation ◽  
Modeling Tool ◽  
Simulation Results ◽  
Internet Networks ◽  
Internet Of Things Technology ◽  
The Internet Of Things

В данной статье предлагается методика повышения защищенности сетей и конечных устройств интернета вещей от атак, направленных на нарушение конфиденциальности информации и процедуры аутентификации, за счет внедрения новых несертифицированных протоколов обеспечения безопасности и создания методического обеспечения для оценки рисков успешной реализации атак. В работе были смоделированы и проанализированы протоколы безопасности технологии интернета вещей с помощью специализированного инструмента моделирования. При использовании результатов моделирования для всех протоколов, представленных в данной работе, был посчитан риск успешной реализации атак, направленных на нарушение конфиденциальности информации и процедуры аутентификации. На основе полученных значений было выполнено сравнение протоколов безопасности. Результаты проделанной работы позволят упростить разработку и внедрение новых протоколов безопасности для технологии интернета вещей. This article proposes a method for improving the security of the networks and end devices of the Internet of Things from attacks aimed at violating the confidentiality of information and authentication procedures by introducing new uncertified security protocols and creating methodological support for assessing the risks of successful implementation of attacks. The security protocols of the Internet of Things technology were modeled and analyzed using a specialized modeling tool. When using the simulation results for all the protocols presented in this work, the risk of successful implementation of attacks aimed at violating the confidentiality of information and the authentication procedure was calculated. Based on the obtained values, a comparison of security protocols was performed. The results of this work will simplify the development and implementation of new security protocols for the Internet of Things technology.

scholarly journals Sports Injury Risk Assessment Based on Blockchain and Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jihua Liu
Keyword(s):  
Blood Pressure ◽  
Risk Assessment ◽  
Body Temperature ◽  
Internet Of Things ◽  
Injury Risk ◽  
Sports Injury ◽  
Wearable Devices ◽  
Physiological Parameters ◽  
Computational Power ◽  
Motion State

With the increase of people’s exercise in today’s society, how to exercise scientifically and healthily has attracted much attention. Therefore, sports injury risk assessment and monitoring system has attracted more and more attention in real-time, flexibility, intelligence, and other aspects. To solve the above problems, this paper proposes a sports injury risk assessment based on blockchain and Internet of Things. By introducing computational power weight, a computational power balance D-H algorithm based on Internet of Things blockchain network architecture is proposed. It can provide a secure and trusted interactive environment for the Internet of Things. On the basis of blockchain and Internet of Things, a multisensor data fusion algorithm is proposed to be applied to the analysis and evaluation of sports injury. A variety of physiological parameters of human motion state are collected through multisensor, the collected physiological parameters are processed by data fusion, and finally, sports injury risk assessment is carried out. The built system takes the embedded esp8266wifi module as the hardware processing core and uses body temperature sensor, blood pressure sensor, EMG sensor, and pulse sensor to form wearable devices. By wearing wearable devices, four human physiological parameters such as body temperature, blood pressure, electromyography, and pulse can be collected. In the process of decision level fusion, different weights are set for the focal elements causing information conflict, and the optimized D-S evidence theory algorithm is used. Thus, according to the data detected by multisensor, the injury risk of user motion state is evaluated.

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