This paper considers the domain of Industrial Internet of Things (IIoT) infrastructures and the recurring need for collaboration across teams and stakeholders by means of remote access. The paper describes a secure solution beyond the traditional perimeter-based security approach, which consists of an architecture that supports multi-level authorization to achieve fine-grained access control, better scalability, and maintainability. An implementation of the proposed solution, using open-source technologies, is also discussed and covers the protection of both the network and edge domains of a complex IIoT infrastructure. Finally, the paper presents a risk-driven and model-based process that is designed to support the migration of existing infrastructures to the solution architecture. The approach is validated, taking as a reference two relevant scenarios for the aerospace industry.

The accurate tracking of every production step and related outcome in a supply chain is a stringent requirement in safety-critical sectors such as civil aviation. In such a framework, trusted traceability and accountability can be reliably and securely managed by means of blockchain-based solutions. Unfortunately, blockchain cannot guarantee the provenance and accuracy of the stored information. To overcome such a limitation, this paper proposes a secure solution to strongly rely on the tracking information of the physical assets in the supply chain. The proposed solution exploits Hardware Security Modules (HSMs) to provide required cryptographic primitives through a Near-Field Communication (NFC) connection. In our approach, each transfer of the assets is authenticated, verified, and recorded in the blockchain through the HSM. Transaction entries are signed, thus providing a guarantee of ownership and authenticity. The proposed infrastructure has been subject of an exhaustive security analysis and proved resilient against counterfeiting attempts, stakeholder repudiations, and misleading information.

Collaborative manufacturing is a key enabler of Industry 4.0 that requires secure data sharing among multiple parties. However, intercompany data-sharing raises important privacy and security concerns, particularly given intellectual property and business-sensitive information collected by many devices. In this paper, we propose a solution that combines four technologies to address these challenges: Attribute-Based Encryption for data access control, blockchain for data integrity and non-repudiation, Hardware Security Modules for authenticity, and the Interplanetary File System for data scalability. We also use OpenID for dynamic client identification and propose a new method for user revocation in Attribute-Based Encryption. Our evaluation shows that the solution can scale up to 2,000,000 clients while maintaining all security guarantees.

Compliance data consists of manufacturing quality measures collected in the production process. Quality checks are most of the times computationally expensive to perform, mainly due to the amount of collected data. Having trusted solutions for outsourcing analyses to the Cloud is an opportunity for reducing costs of operation. However, the adoption of the Cloud computation paradigm is delayed for the many security risks associated with it. In the use case we consider in this paper, compliance data is very sensitive, because it may contain IP-critical information, or it may be related to safety-critical operations or products. While the technological solutions that protect data in-transit or at rest have reached a satisfying level of maturity, there is a huge demand for securing data in-use. Homomorphic Encryption (HE) is one of the main technological enablers for secure computation outsourcing. In the last decade, HE has reached maturity with remarkable pace. However, using HE is still far from being an automated process and each use case introduces different challenges. In this paper, we investigate application of HE to the described scenario. In particular, we redesign the compliance check algorithm to a HE-friendly equivalent. We propose efficient data input encoding that takes advantage of SIMD type of computations supported by the CKKS HE scheme. Moreover, we introduce security/performance trade-offs by proposing limited but acceptable information leakage. We have implemented our solution using SEAL HE library and evaluated our results in terms of time complexity and accuracy. Finally, we analyze the benefits and limitations of integration of a Trusted Execution Environment for secure execution of some computations that are overly expensive for the chosen HE scheme.

Securing resource-constrained Industrial Internet of Things (IIoT) devices requires guarantees of integrity and confidentiality. This paper presents a security framework developed under the CERTIFY project to document and justify trustworthy execution of sensitive software running on resource-constrained devices. Our architecture model assumes the presence of a separation kernel, that employs hardware Memory Protection Units to enforce Memory isolation and mediate communications during boot, provisioning, and run-time. On the other side, the paper does not cover implementation aspects, but leaves them to the choice of the user intending to adopt the proposed solution architecture. To systematically show the trustworthiness of this proposed architecture, we develop an assurance case using Goal Structuring Notation: we map system requirements to architecture-specific security objectives and introduce a novel “attacker action” graphical element to explicitly integrate threat modeling into our arguments. The resulting assurance case provides a structured, auditable, and reusable foundation architecture for the secure implementation of the CERTIFY IIoT framework.