Blockchain-based IoMT for an intelligent healthcare system using a drop-offs queue

Mallick, Soubhagya Ranjan; Goswami, Veena; Lenka, Rakesh Kumar; Sahoo, Tushar Ranjan; Kumar, Vinay; Barik, Rabindra K.

doi:10.1109/mac58191.2023.10176337

Cited by 4 publications

(1 citation statement)

References 20 publications

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“…Blockchain's robustness and features have made integration with various technologies like AI and ML an important area to work on. As various security solutions using blockchain for data have already been proposed, more emphasis is being laid on exploring the possibilities for hardware-assisted blockchain for security [12,45]. Blockchain and Tangle have varied data structures.…”

Section: Overview Of Blockchain Technologymentioning

confidence: 99%

PUFchain 3.0: Hardware-Assisted Distributed Ledger for Robust Authentication in Healthcare Cyber–Physical Systems

Bathalapalli,

Mohanty,

Kougianos

et al. 2024

Sensors

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This article presents a novel hardware-assisted distributed ledger-based solution for simultaneous device and data security in smart healthcare. This article presents a novel architecture that integrates PUF, blockchain, and Tangle for Security-by-Design (SbD) of healthcare cyber–physical systems (H-CPSs). Healthcare systems around the world have undergone massive technological transformation and have seen growing adoption with the advancement of Internet-of-Medical Things (IoMT). The technological transformation of healthcare systems to telemedicine, e-health, connected health, and remote health is being made possible with the sophisticated integration of IoMT with machine learning, big data, artificial intelligence (AI), and other technologies. As healthcare systems are becoming more accessible and advanced, security and privacy have become pivotal for the smooth integration and functioning of various systems in H-CPSs. In this work, we present a novel approach that integrates PUF with IOTA Tangle and blockchain and works by storing the PUF keys of a patient’s Body Area Network (BAN) inside blockchain to access, store, and share globally. Each patient has a network of smart wearables and a gateway to obtain the physiological sensor data securely. To facilitate communication among various stakeholders in healthcare systems, IOTA Tangle’s Masked Authentication Messaging (MAM) communication protocol has been used, which securely enables patients to communicate, share, and store data on Tangle. The MAM channel works in the restricted mode in the proposed architecture, which can be accessed using the patient’s gateway PUF key. Furthermore, the successful verification of PUF enables patients to securely send and share physiological sensor data from various wearable and implantable medical devices embedded with PUF. Finally, healthcare system entities like physicians, hospital admin networks, and remote monitoring systems can securely establish communication with patients using MAM and retrieve the patient’s BAN PUF keys from the blockchain securely. Our experimental analysis shows that the proposed approach successfully integrates three security primitives, PUF, blockchain, and Tangle, providing decentralized access control and security in H-CPS with minimal energy requirements, data storage, and response time.

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Section: Overview Of Blockchain Technologymentioning

confidence: 99%

PUFchain 3.0: Hardware-Assisted Distributed Ledger for Robust Authentication in Healthcare Cyber–Physical Systems

Bathalapalli,

Mohanty,

Kougianos

et al. 2024

Sensors

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Blockchain-Integrated Security for Real-Time Patient Monitoring in the Internet of Medical Things Using Federated Learning

Khan,

Abaoud

2023

IEEE Access

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The Internet of Medical Things (IoMT) heralds a transformative era in healthcare, with the potential to revolutionize patient care, healthcare services, and medical research. As with all technological progressions, IoMT introduces a suite of complex challenges, predominantly centered on security. In particular, ensuring the integrity, confidentiality, and availability of health data in real-time communication stands paramount, given the sensitivity of the information and the ramifications of potential breaches or misuse. In light of these challenges, existing security frameworks, while commendable, exhibit limitations. Specifically, they often grapple with comprehensive anomaly detection, effective resistance to replay attacks, and robust protection against threats like man-in-the-middle attacks, eavesdropping, data tampering, and identity spoofing. The proposed framework integrates state-of-the-art encryption techniques, cuttingedge pattern recognition modules, and adaptive learning mechanisms. These components collaboratively ensure data integrity during transmission, provide robust resistance against conventional and novel attack vectors, and adapt to evolving threats through continuous learning. Moreover, the framework incorporates sophisticated checksum techniques and advanced behavioral analysis, further enhancing its protective capabilities. Our system demonstrated significant improvements in anomaly detection and attack resistance metrics, consistently outperforming benchmark solutions like MRMS and BACKM-EHA.

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Analysing Security Threats And Elevating Healthcare Privacy For A Resilient Future

Gupta,

Kumar

et al. 2023

2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI)

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Blockchain-based IoMT for an intelligent healthcare system using a drop-offs queue

Cited by 4 publications

References 20 publications

PUFchain 3.0: Hardware-Assisted Distributed Ledger for Robust Authentication in Healthcare Cyber–Physical Systems

PUFchain 3.0: Hardware-Assisted Distributed Ledger for Robust Authentication in Healthcare Cyber–Physical Systems

Blockchain-Integrated Security for Real-Time Patient Monitoring in the Internet of Medical Things Using Federated Learning

Analysing Security Threats And Elevating Healthcare Privacy For A Resilient Future

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