Assessment of IIoT Sensor Security Vulnerabilities in Digital Wine Manufacturing Leveraging the CVSS

Integrating IIoT into manufacturing has significantly enhanced connectivity and production precision, but it also introduces a complex cybersecurity landscape, particularly in digital manufacturing systems. Current vulnerability assessment tools are often system-specific and need more scalability fo...

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Veröffentlicht in:IEEE access 2024, Vol.12, p.141489-141513
Hauptverfasser: Sen, Sachin K., Karmakar, Gour C., Pang, Shaoning
Format: Artikel
Sprache:eng
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Zusammenfassung:Integrating IIoT into manufacturing has significantly enhanced connectivity and production precision, but it also introduces a complex cybersecurity landscape, particularly in digital manufacturing systems. Current vulnerability assessment tools are often system-specific and need more scalability for large IIoT networks. While CVSS offers a standardized framework for assessing vulnerabilities across entire systems, practical adaptations for specific manufacturing contexts are yet to be developed. To address this gap, we present a novel framework to evaluate CVSS impact metrics tailored to the unique environmental and operational contexts of wine manufacturing. This approach leverages the correlation between wine characteristics and quality to assess potential threats and vulnerability exposures in IIoT wine sensors. Our findings show that vulnerability scores derived from CVSS 4.0 demonstrate greater resilience against cyber-attacks than CVSS 3.1 due to the incorporation of newly developed system impact and threat metric assessments. A pair-wise t-test reveals a significant difference between CVSS 4.0 and 3.1 scores, with a p-value of 0.002, highlighting the comprehensiveness of CVSS 4.0 that incorporates system impact and threat metric values assessed by our proposed framework. The proposed methodology is adaptable for evaluating security vulnerabilities in various manufacturing systems, tailored to their specific applications and deployment contexts.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3467248