A Stochastic Approach of Dependency Evaluation for IoT Devices

Huang, Jiwei; Chen, Guo; Cheng, Bowen

doi:10.1049/cje.2016.03.003

Cited by 11 publications

(4 citation statements)

References 15 publications

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“…A network-based approach can also assist the evaluation of physical dependencies and cascading disruptions within and across geographical dimensions. These typically explore stochastic modelling 147,151 , especially the Markov-based techniques 152,153 . An important point to draw from these approaches is that topological characteristics of networked infrastructures, such as connectivity, path length, degree of vertex, and redundancy ratio can be leveraged for interdependency analysis, and used to resolve the spatial impacts of risks and disruptions in the IoT.…”

Section: Iot Risk Analysis Through Functional Dependencymentioning

confidence: 99%

Cyber Risk Management for the Internet of Things

Radanliev¹,

D²,

Burnap³

et al. 2019

Preprint

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The Internet-of-Things (IoT) enables enterprises to obtain profits from data but triggers data protection questions and new types of cyber risk. Cyber risk regulations for the IoT however do not exist. The IoT risk is not included in the cyber security assessment standards, hence, often not visible to cyber security experts. This is concerning, because companies integrating IoT devices and services need to perform a self-assessment of its IoT cyber security posture. The outcome of such self-assessment need to define a current and target state, prior to creating a transformation roadmap outlining tasks to achieve the stated target state. In this article, a comparative empirical analysis is performed of multiple cyber risk assessment approaches, to define a high-level potential target state for company integrating IoT devices and/or services. Defining a high-level potential target state represent is followed by a high-level transformation roadmap, describing how company can achieve their target state, based on their current state. The transformation roadmap is used to adapt IoT risk impact assessment with a Goal-Oriented Approach and the Internet of Things Micro Mart model. The main contributions from this paper represent a transformation roadmap for standardisation of IoT risk impact assessment; and transformation design imperatives describing how IoT companies can achieve their target state based on their current state with a Goal-Oriented approach. Verified by epistemological analysis defining a unified cyber risk assessment approach. These can be used for calculating the economic impact of cyber risk; for international cyber risk assessment approach; for quantifying cyber risk; and for planning for impact of cyber-attacks, e.g. cyber insurance. The new methods presented in this paper for applying the roadmap include: IoT Risk Analysis through Functional Dependency; Network-based Linear Dependency Modelling; IoT risk impact assessment with a Goal-Oriented Approach; and a correlation between the Goal-Oriented Approach and the IoTMM model.

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Section: Iot Risk Analysis Through Functional Dependencymentioning

confidence: 99%

Cyber Risk Management for the Internet of Things

Radanliev¹,

D²,

Burnap³

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…For the perception layer, various sensors, actuators, RFID tags, and other ''things'' are connected to the IoT with specific interfaces. 4 Network layer is responsible to establish the communication between ''things'' and humans. Currently, Ethernet and wireless local area networks (WLAN) are widely used in different application environments of IoT, and some new communication technologies such as narrow band Internet of Things (NB-IoT) are becoming more and more popular.…”

Section: Introductionmentioning

confidence: 99%

A reconfigurable smart interface based on IEEE 1451 and field programmable gate array for multiple Internet of Things devices

Wang

Hou

Gao

et al. 2017

International Journal of Distributed Sensor Networks

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The Internet of Things is becoming increasingly important in traffic, medical treatment, and other industry fields. With the development of the Internet of Things technology, lots of new ''things'' need to be accessed to the Internet of Things. Currently, Internet of Things applications adopt multiple methods to access the heterogeneous devices. How to provide unified access means for those ''things'' is a fundamental issue. To solve this problem, a new method is proposed in this article to design a reconfigurable smart interface for multiple Internet of Things devices. The IEEE 1451 standard is adopted for this design, and it comprehensively specifies the smart transducer design and relevant interface protocol to implement the intelligent acquisition for common sensors and actuators. Field programmable gate array is adopted for the implementation of this design to reduce consumption of resources and enable the reconfiguration of the whole system. Performance of the proposed system is evaluated, and good performance is achieved in practical application for office environment monitoring.

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“…However, the more common approach involves the networkbased approach, which can assist with evaluating physical dependencies and cascading disruptions within and across geographical dimensions. These typically explore stochastic modelling (Bloomfield et al 2010;Huang et al 2016), especially the Markov-based undirected techniques (Nozick et al 2004;Qiao et al 2007), and the Bayesian Networkbased (BN) technique (Di Giorgio and Liberati 2011). This BN approach appears more promising for demonstrating the characteristics of components and dependencies in the IoT network, thus is discussed further.…”

Section: Network-based Linear Dependency Modellingmentioning

confidence: 99%

Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems: cyber risk at the edge

et al. 2020

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The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.

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A Stochastic Approach of Dependency Evaluation for IoT Devices

Cited by 11 publications

References 15 publications

Cyber Risk Management for the Internet of Things

Cyber Risk Management for the Internet of Things

A reconfigurable smart interface based on IEEE 1451 and field programmable gate array for multiple Internet of Things devices

Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems: cyber risk at the edge

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