Hospitals produce vast amounts of medical device data, making their protection and analysis crucial in Cyber Threat Intelligence (CTI) settings. MedTech Chain 1.0 allowed cybersecurity researchers to run queries for data analytics. Even if the platform applied differential privacy, data storage was in plaintext and certain analysis capabilities were still missing. To address these limitations, we propose MedTech Chain 2.0, a platform that integrates homomorphic encryption, and enhanced mechanisms for encryption key management, and expanded query support. These improvements strengthen data protection while enabling deeper insights, advancing in cybersecurity and CTI research.

Employing online identity management technologies and the use of blockchain capabilities, Gryphon is aimed at providing a decentralized Digital Identity Management System that securely handles user data by using Hyperledger Fabric. By introducing Trustchain, the system enables the verification of user credentials through modular components, facilitating streamlined and privacy-preserving communication between parties that require mutual data exchange. Gryphon is among the first platforms to implement this form of identity communication using the Hyperledger Fabric framework, demonstrating its viability as a foundation for decentralized identity management.

Today, there is an increasing need for an efficient threshold signatures that enforce the protection of identities and multi device-based authentication when interacting with a blockchain technology. This study presents a comprehensive analysis of threshold signatures, establishing FROST as the most efficient scheme in terms of performance. We uniquely demonstrate FROST’s adaptability with empirical results, showcasing its feasibility on middle-range IoT devices and smartphones. In addition we propose an implementation, with a primary goal to enable IoT devices interaction with Hyperledger Fabric v3.0 using FROST for transaction signing. An IoT network of 5 devices can perform a signature and commit to the blockchain ledger in 3.2 seconds, when network latency is optimal.

Employing blockchain and privacy-enhancing technologies, MedTech Chain promises an authenticated, decentralised, secure, and privacy-preserving environment for the real-time research and monitoring of medical device data. Through its querying functionalities, the platform can provide valuable insights for threat intelligence, medical research and hospital management. To our knowledge, the approach is among the first to employ ϵ-differential privacy in the context of medical device data. The current work details the framework’s functionality and demonstrates a negligible time overhead induced by ϵ-differential privacy to data analysis.

Rapid advancements in digital medical technologies have significantly improved patient care but have also raised complex security and privacy challenges. Traditional tools for detecting vulnerabilities in networked medical devices, primarily used by network administrators and security specialists, have become insufficient due to their large-scale use across the entire healthcare network. Aiming to improve security in healthcare, MedTech Chain proposes a way to solve this challenge by leveraging blockchain and privacy-enhancing technologies, offering an authenticated, decentralised, secure, and privacy-preserving environment for the research and monitoring of medical device data. Currently, the framework enables counting, averaging, and grouped counting queries with multiple filtering capabilities like time frame and location. Such functionalities can provide valuable insights not only for threat intelligence but also for medical research and hospital management. MedTech Chain is modular and flexible, designed to seamlessly extend to new device technologies and research demands. To our knowledge, the approach is among the first to employ ϵ-differential privacy in the context of medical device data.

Employing blockchain and privacy-enhancing technologies, MedTech Chain promises an authenticated, decentralised, secure, and privacy-preserving environment for the real-time research and monitoring of medical device data. Through its querying functionalities, the platform can provide valuable insights for threat intelligence, medical research and hospital management. To our knowledge, the approach is among the first to employ ϵ-differential privacy in the context of medical device data. The current work details the framework's functionality and demonstrates a negligible time overhead induced by ϵ-differential privacy to data analysis.

Blockchain’s potential to revolutionize supply chain and logistics with transparency and equitable stakeholder engagement is significant. However, challenges like scalability, privacy, and interoperability persist. This study explores the scarcity of real-world blockchain implementations in supply chain and logistics since we have not witnessed many real-world deployments of blockchain-based solutions in the field. Puzzled by this, we integrate technology, user experience, and operational efficiency to illuminate the complex landscape of blockchain integration. We present blockchain-based solutions in three use cases, comparing them with alternative designs and analyzing them in terms of technical, economic, and operational aspects. Insights from a tailored questionnaire of 50 questions addressed to practitioners and experts offer crucial perspectives on blockchain adoption. One of the key findings from our work shows that half of the companies interviewed agree that they will miss the potential for competitive advantage if they do not invest in blockchain technology, and 61% of the companies surveyed claimed that their customers ask for more transparency in supply chain-related transactions. However, only one-third of the companies were aware of the main features of blockchain technology, which shows a lack of knowledge among the companies that may lead to a weaker blockchain adaption in supply chain use cases. Our readers should note that our study is specifically contextualized in a Netherlands-funded national project. We hope that researchers as well as stakeholders in supply chain and logistics can benefit from the insights of our work.

Recent literature claims that blockchain technology (BCT) has the potential to enhance interorganizational data sharing. Yet, in practice, BCTs implementation faces challenges that partly explain companies' reluctance to adopt BCT in their existing interorganizational environment. This is particularly striking in some economic sectors, such as the automotive industry transformed by the current digital servitization (DS) of the connected vehicle ecosystem; where traditional automotive businesses are being urged to collaborate with new ecosystem actors (e.g., insurance companies). With the perspective to tackle these challenges and promote the use of BCT at the interorganizational level, this article designs a BCT-based architecture based on Polkadot. Based on a design science research approach, we ensure alignment between the technological, interorganizational, and organizational dimensions of DS. Results are drawn from a dialog with the connected vehicle ecosystem's actors as well as a literature review at the intersection of BCT design, DS, and data sharing. Overall, results contribute to the existing literature on BCT design, as they emphasize the potential of multichain BCT to structure interorganizational settings. Additionally, the study provides design principles for integrating BCT into data-sharing contexts like the one observed in the connected vehicle ecosystem. More specifically, this research emphasizes the suitability of multichain architecture in allowing a balance between the decentralization of public blockchains and the control of private blockchains.

Medical research benefits from large quantities of high-quality data. Internet-based data-sharing platforms bring the advantage of rapidly sharing data medical data. However, ensuring security and accountability in networked medical systems remains a challenge. In this paper, we propose a secure and auditable data-sharing platform for hospitals and research groups based on a distributed ledger. A two-party protocol for recoverable key agreement lies at the basis of securing the data sharing. This protocol enables two parties to agree on an encryption key and put the encryption key under the escrow of a board of semi-trusted auditors. A quorum of these auditors is required in order to recover the encryption key. The recoverable key agreement ensures that past communication can be audited, even if one of the two parties is malicious. We provide a realization of the protocol and analyze its complexity and performance. Based on these analyses, we demonstrate that the protocol is suitable for real-world use cases and resource-constrained devices.

More and more IoT use cases require trustworthy computing from cloud/back-end services, which cannot necessarily provide a fully trusted execution environment, data immutability, and traceability. The integration of IoT with the blockchain technology is one of the most promising solutions to achieve the previously mentioned features in the IoT networks. Researchers are also interested in integration solutions, and several solutions are already present in the scientific literature. However, there are still some uncertainties in establishing a direct and effective interaction between an IoT device and the given blockchain. In this work, we propose the first IoT hardware architecture model designed to accelerate time-consuming operations of IoT-Blockchain. The proposed IoT hardware architecture model is programmed in SystemC-TLM and can provide a significant reduction in execution time, 53% and 18% when running Hyperledger Sawtooth and Ethereum applications, respectively.

We present in this work a Lightweight Transaction Protocol (LTP) for enabling constrained embedded devices’ interaction with multiple types of blockchains via the LoRaWAN communication protocol. The proposed protocol provides the benefit of interacting with multiple blockchains with only 13.5% decrease in battery life. The protocol also includes a gateway module API that connects to blockchains and generic smart contracts to authenticate end devices and store their data. The study points out that, in the worst case, end-device data can be stored in blockchains with a latency of 20.3 seconds for Substrate and 6.8 seconds for the Hyperledger Fabric blockchain.

This work aims to provide a more secure access control in Hyperledger Fabric blockchain by combining multiple ID’s, attributes, and policies with the components that regulate access control. The access control system currently used by Hyperledger Fabric is first completely analyzed. Next, a new implementation is proposed that builds upon the existing solution but provides users and developers with easier ways to make access control decisions based on combinations of multiple ID’s, attributes, and policies. Our proposed implementation encapsulates the Fabric CA client to facilitate attribute addition and simplify the process of registering and enrolling a newly created certificate (corresponding to a new user). This research, concludes that it is possible to combine multiple ID’s, attributes, and policies with the help of Hyperledger Fabric’s smart contract technology. Furthermore, it could be seen that the performance impact for real-world applications is negligible compared to the insecure case of always providing access to a resource without performing access control.

This paper offers a prototype of a Hyperledger Fabric-IPFS based network architecture including a smart contract based encryption scheme that meant to improve the security of user’s data that is being uploaded to the distributed ledger. A new extension to the self-encryption scheme was deployed by integrating data owner’s identity into the encryption process. Such integration allows to permanently preserve ownership of the original file and link it to the person/entity who originally uploaded it. Moreover, self-encryption provides strong security guarantees that decryption of a file is computationally not feasible under the condition that the encrypted file and the key are safely stored.