A Tutorial on the Implementation of a Hyperledger Fabric-based Security Architecture for IoMT

Abstract

Internet of Medical Things (IoMT) have improved individuals' quality of life by enabling IoMT-based healthcare monitoring systems to grow dramatically in recent years. Therefore, cutting-edge security techniques are needed to address the security risks of IoMT networks effectively and in a timely manner. On the other hand, blockchain technology has the potential to play a significant role in both securing IoMT devices and preventing unauthorized access during data transmission and it has been anticipated by the industry and the research community to be a disruptive technology that can be incorporated into novel security solutions for IoMT networks. In this regard, the goal of this research work is to demonstrate the integration of blockchain technology into novel security solutions for IoMT networks and to deploy a Hyperledger Fabric-based blockchain security architecture for IoMT-based healthcare monitoring systems by utilizing the features of the Hyperledger Fabric Platform, its utilities, and its lightweight consensus nature in order to: i) improve security in IoMT-based healthcare monitoring systems, ii) provide secure data storage in a decentralized way, and iii) eliminate single point of failure.

Automated Over-the-Top Service Copyright Distribution Management System Using the Open Digital Rights Language

“…Additionally, when composing chaincode, it allows configurations based on general programming languages, ensuring versatility. It also guarantees confidentiality and privacy by allowing only the authorized peers participating in the channel to access the data [6][7][8][9][10].…”

“…As can be seen in Figure 1, various components operate organically on the Hyperledger Fabric network [6]. Table 1 below shows the main roles of components in the Hyperledger Fabric architecture [6][7][8][9][10]. In the case of transaction processing and recording in the ledger based on the components in Figure 1, operations between components are performed as shown in Figure 2.…”

“…(8) Signatory participant v i selects t values from c v i , calculates e ≡ H(M, Π v k ∈P c v k modp) and y v i ≡ r v i + s v i e mod q, and sends the resulting pair (e, y v i ) to the signature aggregator. (9) The signature aggregator compiles the final signature value (y, e) by processing the t partial signatures (e, y v i ) with the same e value. (10) The verifier conducts signature verification using the received signature value (e, y), following the same method as the Schnorr Digital Signature, by calculating H(M, C ≡ g y ) * V e mod p.…”

“…In this paper, the proposed automated OTT service copyright distribution management system using the ODRL stipulates that copyright distribution transactions proceed only when all copyright holders have signed. Consequently, for the computational requirements of generating and verifying Threshold Schnorr Digital Signature, the threshold has been set equal to the number of signatory participants, denoted as n. (n − 1)n Process (3) (32n − 3)n Process (4) (n − 1)n Process (5) (32n − 3)n Process (6) -Process (7) (1.5k − 1)n Process (8) n Process (9) 0 Process (10) 3k…”

“…In Step (8), there are a total of n multiplications executed, comprising of n − 1 multiplications to calculate e ≡ H(M, Π v k ∈P c v k modp) and an additional single multiplication for y v i ≡ r v i + s v i e mod q. For Step (9), which involves combining partial signatures into a single signature, only addition is used, resulting in a multiplication workload of zero in the Square-and-Multiply algorithm.…”