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In modern industrial production lines, the integration and interconnection of various different manufacturing components, like robots, laser cutting machines, milling machines, CNC-machines, etc. allows for a higher degree of autonomous production on the shop floor. Manufacturers of these increasingly complex machines are beginning to equip their business models with bidirectional data flows to other factories. This is creating a digital, cross-company shop floor infrastructure where the transfer of information is controlled by digital contracts. To establish a trusted ecosystem, the new technology "blockchain" and a variety of technology stacks must be combined while ensuring security. Such blockchain-based frameworks enable bidirectional trust across all contract partners. Essential data flows are defined by specific technical representation of contract agreements and executed through smart contracts.This work describes a platform for rapid cross-company business model instantiation based on blockchain for establishing trust between the enterprises. It focuses on selected security aspects of the deployment- and configuration processes applied by the industrial ecosystem. A threat analysis of the platform shows the critical security risks. Based on an industrial dynamic machine leasing use case, a risk assessment and security analysis of the key platform components is carried out.
In edge/fog computing infrastructures, the resources and services are offloaded to the edge and computations are distributed among different nodes instead of transmitting them to a centralized entity. Distributed Hash Table (DHT) systems provide a solution to organizing and distributing the computations and storage without involving a trusted third party. However, the physical locations of nodes are not considered during the creation of the overlay which causes some efficiency issues. In this paper, Locality aware Distributed Addressing (LADA) model is proposed that can be adopted in distributed infrastructures to create an overlay that considers the physical locations of participating nodes. LADA aims to address the efficiency issues during the store and lookup processes in DHT overlay. Additionally, it addresses the privacy issue in similar proposals and removes any possible set of fixed entities. Our studies showed that the proposed model is efficient, robust and is able to protect the privacy of the locations of the participating nodes.