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.