Interoperability and Integration Testing Methods for IoT Systems: A Systematic Mapping Study

Bureš, Miroslav; Klima, Matej; Rechtberger, Vaclav; Bellekens, Xavier; Tachtatzis, Christos; Atkinson, Robert; Ahmed, Bestoun S.

doi:10.1007/978-3-030-58768-0_6

Cited by 21 publications

(7 citation statements)

References 52 publications

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“…The graphs presented in Figure 1 a–c depict the evolution of the number of publications from 2015 to 2020 on Test-Beds in the Internet-of-Things (IoT), Smart Grid and Cloud disciplines. Increases in the number of publications for all domains is clearly evident, demonstrating extensive research in cyber-security and Test-beds [ 15 ].…”

Section: Methodsmentioning

confidence: 99%

A Review of Cyber-Ranges and Test-Beds: Current and Future Trends

Ukwandu

Farah

Hindy

et al. 2020

Sensors

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Cyber situational awareness has been proven to be of value in forming a comprehensive understanding of threats and vulnerabilities within organisations, as the degree of exposure is governed by the prevailing levels of cyber-hygiene and established processes. A more accurate assessment of the security provision informs on the most vulnerable environments that necessitate more diligent management. The rapid proliferation in the automation of cyber-attacks is reducing the gap between information and operational technologies and the need to review the current levels of robustness against new sophisticated cyber-attacks, trends, technologies and mitigation countermeasures has become pressing. A deeper characterisation is also the basis with which to predict future vulnerabilities in turn guiding the most appropriate deployment technologies. Thus, refreshing established practices and the scope of the training to support the decision making of users and operators. The foundation of the training provision is the use of Cyber-Ranges (CRs) and Test-Beds (TBs), platforms/tools that help inculcate a deeper understanding of the evolution of an attack and the methodology to deploy the most impactful countermeasures to arrest breaches. In this paper, an evaluation of documented CRs and TBs platforms is evaluated. CRs and TBs are segmented by type, technology, threat scenarios, applications and the scope of attainable training. To enrich the analysis of documented CRs and TBs research and cap the study, a taxonomy is developed to provide a broader comprehension of the future of CRs and TBs. The taxonomy elaborates on the CRs/TBs dimensions, as well as, highlighting a diminishing differentiation between application areas.

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Section: Methodsmentioning

confidence: 99%

A Review of Cyber-Ranges and Test-Beds: Current and Future Trends

Ukwandu

Farah

Hindy

et al. 2020

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…The graphs presented in Figures 1a, 1b and 1c depict the evolution of the number of publications from 2015 to 2020 on Test-beds in the Internet-of-Things (IoT), Smart Grid and Cloud disciplines. Increases in the number of publications for all domains is clearly evident, demonstrating extensive research in cyber-security and Test-beds [4].…”

Section: Selection Criteriamentioning

confidence: 96%

A Review of Cyber-Ranges and Test-Beds: Current and Future Trends

Ukwandu¹,

Farah²,

Hindy³

et al. 2020

Preprint

Self Cite

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Cyber situational awareness has been proven to be of value in forming a comprehensive understanding of threats and vulnerabilities within organisations, as the degree of exposure is governed by the prevailing levels of cyber-hygiene and established processes. A more accurate assessment of the security provision informs on the most vulnerable environments that necessitate more diligent management. The rapid proliferation in the automation of cyber-attacks is reducing the gap between information and operational technologies and the need to review the current levels of robustness against new sophisticated cyber-attacks, trends, technologies and mitigation countermeasures has become pressing. A deeper characterisation is also the basis with which to predict future vulnerabilities in turn guiding the most appropriate deployment technologies. Thus, refreshing established practices and the scope of the training to support the decision making of users and operators. The foundation of the training provision is the use of Cyber-Ranges (CRs) and Test-Beds (TBs), platforms/tools that help inculcate a deeper understanding of the evolution of an attack and the methodology to deploy the most impactful countermeasures to arrest breaches. In this paper, an evaluation of documented CR and TB platforms is evaluated. CRs and TBs are segmented by type, technology, threat scenarios, applications and the scope of attainable training. To enrich the analysis of documented CR and TB research and cap the study, a taxonomy is developed to provide a broader comprehension of the future of CRs and TBs. The taxonomy elaborates on the CRs/TBs different dimensions, as well as, highlighting a diminishing differentiation between application areas.

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“…For the past decade, there has been significant development of solutions for a wide range of devices and AIoT platforms (Bures et al , 2020). However, this has posed an interoperability issue, as each solution comes with its own platform, devices, application programming interfaces and file formats.…”

Section: Integration Of Artificial Intelligence Of Things In the Publ...mentioning

confidence: 99%

Integration of artificial intelligence of things (AIoT) in the public sector: drivers, barriers and future research agenda

Ishengoma

Shao²,

Alexopoulos³

et al. 2022

DPRG

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Purpose With the development of information technology (IT), governments around the globe are using state-of-the-art IT interfaces to implement the so-called 3E’s in public service delivery, that is, economy, efficiency and effectiveness. Two of these IT interfaces relate to Artificial Intelligence (AI) and Internet of Things (IoT). While AI focuses on providing a “human” garb for computing devices, thereby making them “intelligent” devices, IoT relies on interfaces between sensors and the environment to make “intelligent” decisions. Recently, the convergence of AI and IoT – also referred to as Artificial Intelligence of Things (AIoT) – is seen as a real opportunity to refurbish the public service delivery formats. However, there is limited understanding as to how AIoT could contribute to the improvisation of public service delivery. This study aims to create a modular framework for AIoT in addition to highlighting the drivers and barriers for its integration in the public sector. Design/methodology/approach This descriptive-explanatory study takes a qualitative approach. It entails a thorough examination of the drivers and barriers of integrating AI and IoT in the public sector. A review of literature has led to the development of a conceptual framework outlining the various factors that contribute to creating public value. Findings Value creation occurs when AI and IoT coalesce in the public service delivery mechanisms. Originality/value AIoT is a cutting-edge technology revolutionizing health care, agriculture, infrastructure and all other industrial domains. This study adds to the growing body of knowledge on the public sector's use of AI and IoT. Understanding these disruptive technologies is critical to formulating policies and regulations that can maximize the potential benefits for the public-sector organizations.

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Interoperability and Integration Testing Methods for IoT Systems: A Systematic Mapping Study

Cited by 21 publications

References 52 publications

A Review of Cyber-Ranges and Test-Beds: Current and Future Trends

A Review of Cyber-Ranges and Test-Beds: Current and Future Trends

A Review of Cyber-Ranges and Test-Beds: Current and Future Trends

Integration of artificial intelligence of things (AIoT) in the public sector: drivers, barriers and future research agenda

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