Abstract
The Industrial Internet of Things (IIoT) is leading to increasingly-interconnected and networked industrial processes and environments, which, in turn, results in stakeholders gathering vast amounts of information. Although the global sharing of information and industrial collaborations in the IIoT promise to enhance productivity, sustainability, and product quality, among other benefits, most information is still commonly encapsulated in local information silos. In addition to interoperability issues, confidentiality concerns of involved stakeholders remain the main obstacle to fully realizing these improvements in practice as they largely hinder real-world industrial collaborations today. Therefore, this dissertation addresses this mission-critical research gap. Since existing approaches to privacy-preserving information sharing are not scalable to industry-sized applications in the IIoT, we present solutions that enable secure collaborations in the IIoT while providing technical (confidentiality) guarantees to the involved stakeholders. Our research is crucial (i) for demonstrating the potential and added value of (secure) collaborations and (ii) for convincing cautious stakeholders of the usefulness and benefits of technical building blocks, enabling reliable sharing of confidential information, even among direct competitors. Our interdisciplinary research thus focuses on establishing and realizing secure industrial collaborations in the IIoT. In this regard, we study two overarching angles of collaborations in detail. First, we distinguish between collaborations along and across supply chains, with the former type entailing more relaxed confidentiality requirements. Second, whether or not collaborators know each other in advance implies different levels of trust and requires different technical guarantees. We rely on well-established building blocks from private computing (i.e., privacy-preserving computation and confidential computing) to reliably realize secure collaborations. We thoroughly evaluate each of our designs, using multiple real-world use cases from production technology, to prove their practical feasibility for the IIoT. By applying private computing, we are indeed able to secure collaborations that not only scale to industry-sized applications but also allow for use case-specific configurations of confidentiality guarantees. In this dissertation, we use well-established building blocks to assemble novel solutions with technical guarantees for all types of collaborations (along and across supply chains as well as with known or unknown collaborators). Finally, on the basis of our experience with engineers, we have derived a research methodology for future use that structures the process of interdisciplinary development and evaluation of secure collaborations in the evolving IIoT. Overall, given the aforementioned improvements, our research should greatly contribute to convincing even cautious stakeholders to participate in (reliably-secured) industrial collaborations. Our work is an essential first step toward establishing widespread information sharing among stakeholders in the IIoT. We further conclude: (i) collaborations can be reliably secured, and we can even provide technical guarantees while doing so; (ii) building blocks from private computing scale to industrial applications and satisfy the outlined confidentiality needs; (iii) improvements resulting from industrial collaborations are within reach, even when dealing with cautious stakeholders; and (iv) the interdisciplinary development of sophisticated yet appropriate designs for use case-driven secure collaborations can succeed in practice.
