IPFS-blockchain-based delegation model for internet of medical robotics things telesurgery system

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Abstract

The concept of the Internet of Medical Robotics Things (IoMRT) is where intelligent robots assess surrounding events, combine information from their sensors, use both local and dispersed intelligence to determine the best course of action, and move or command objects. Telesurgery is one application of IoMRT (TS). With 5G-enabled Tactile Internet (TI) enabling telesurgery (TS), there is ample opportunity to provide exceptional, accurate, ultra-responsive, and real-time virtual surgical procedures. The potential for accurate surgical diagnosis involving the exchange of patient electronic medical records (EMR) with several doctors using an assistant robot (AR) could be greatly useful in the medical field. As a part of this, permission delegation has emerged as a novel approach for data sharing in TI. Robust control of access guidelines combined with a configurable permission scheme promise secure EMR exchange. The present research proposes a multi-hop permission delegation strategy for EMR exchange based on blockchain technology and with configurable delegation depth. Furthermore, the original EMRs are stored on the interplanetary file system (IPFS). Permission delegation uses smart contracts and proxy re-encryption technology. Attribute-based encryption, which offers fine-grained management of access, is used to guarantee data security. Blockchain is also utilized to accomplish immutability and traceability. Delegators may regulate the depth of delegation by using smart contracts. The suggested approach satisfies the intended aims, according to analysis of the protocol. Lastly, the Ethereum test chain is used to assess and put the suggested method into practice. The outcomes of the conducted experiments demonstrate that the suggested protocol operates better than the competitors.

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APA

Basudan, S. (2024). IPFS-blockchain-based delegation model for internet of medical robotics things telesurgery system. Connection Science, 36(1). https://doi.org/10.1080/09540091.2024.2367549

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