IIC Journal of Innovation 9th Edition | Page 131

The Resilience Model Supporting IIoT System Trustworthiness (6). This makes the value of P true. This is how these techniques and approaches help to achieve the resilience goals considered earlier in this article. environment and constraints. These approaches and techniques are considered active because they influence the factors determining resilience according to (6). The approaches listed in Table E-1 of the Draft NIST Special Publication 800-160 VOLUME 2 may be implemented either at design phase or at runtime. Not all approaches can be implemented for every given system. Depending on the initial state and functional constraints the stakeholders may consider the options of how to increase system resilience. The classification shown in the Table 1 helps to clarify these options. Approaches implemented at design phase provide the foundation for building resilience capacity. These approaches and techniques are mostly passive. They set up the types and appropriate ranges for the factors of the generalized predicate P in (6). Approaches used at runtime help in dynamic realignment of algorithms, resources and data according to dynamically changing Table 1 – Classification of resilience approaches and techniques according to the proposed model Factors Active resilience techniques and Passive resilience techniques and approaches implemented at approaches implemented at design runtime phase ST Non-Persistent Services / NP Consistency Analysis / CD Algorithmic structure of the functions determining the control process behavior Non-Persistent Connectivity / NP Orchestration / CD Dynamic Segmentation Isolation / Se and Architectural Diversity / Di Design Diversity / Di Temporal Unpredictability / Up Contextual Unpredictability / Up Synthetic Diversity / Di Supply Chain Diversity / Di Distributed Functionality / DP Restriction / Ra Replacement / Ra Specialization / Ra Predefined Segmentation / Se September 2018 - 126 -