Title | Trustworthiness in Supply Chains : A modular extensible Approach applied to Industrial IoT |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Neises, J., Moldovan, G., Walloschke, T., Popovici, B. |
Conference Name | 2020 Global Internet of Things Summit (GIoTS) |
Date Published | jun |
Keywords | automatable trust models, automatically verifiable operations, behaviour-based context-based, composability, computer network security, Configurability, cross-company Industry, dynamic assessment, dynamic evaluation, dynamically evaluable form, Industrial Internet Consortium, Industrial Internet Security Framework, Industrial IoT, Internet of Things, Metrics, modular extensible approach, modular model, production engineering computing, profile, pubcrawl, regulatory requirements, supply chain management, Supply chains, Trusted Computing, trustworthiness, trustworthiness profiles, trustworthy operation, utility calculation |
Abstract | Typical transactions in cross-company Industry 4.0 supply chains require a dynamically evaluable form of trustworthiness. Therefore, specific requirements on the parties involved, down to the machine level, for automatically verifiable operations shall facilitate the realization of the economic advantages of future flexible process chains in production. The core of the paper is a modular and extensible model for the assessment of trustworthiness in industrial IoT based on the Industrial Internet Security Framework of the Industrial Internet Consortium, which among other things defines five trustworthiness key characteristics of NIST. This is the starting point for a flexible model, which contains features as discussed in ISO/IEC JTC 1/AG 7 N51 or trustworthiness profiles as used in regulatory requirements. Specific minimum and maximum requirement parameters define the range of trustworthy operation. An automated calculation of trustworthiness in a dynamic environment based on an initial trust metric is presented. The evaluation can be device-based, connection-based, behaviour-based and context-based and thus become part of measurable, trustworthy, monitorable Industry 4.0 scenarios. Finally, the dynamic evaluation of automatable trust models of industrial components is illustrated based on the Multi-Vendor-Industry of the Horizon 2020 project SecureIoT. (grant agreement number 779899). |
DOI | 10.1109/GIOTS49054.2020.9119580 |
Citation Key | neises_trustworthiness_2020 |