Deep intelligent blockchain technology for securing IoT-based healthcare multimedia data

Karthik, G; Kumar, Amit; Karri, Aruna Bhaskar; Jagini, Naga Padmaja

doi:10.1007/s11276-023-03333-5

Cited by 7 publications

(3 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It offers off-chain storage for the records and assuring the authenticity and integrity of the health records. In [21], a new hybrid Elman Neural-based Blowfish BC approach has been introduced for the security of the healthcare data in the IoT environment. The Elman network offered continual monitoring to predict abnormal activities in the trained multimedia data.…”

Section: Related Workmentioning

confidence: 99%

Internet of Medical Things with a Blockchain-Assisted Smart Healthcare System Using Metaheuristics with a Deep Learning Model

Albakri

Alqahtani

2023

Applied Sciences

View full text Add to dashboard Cite

The Internet of Medical Things (IoMT) is a network of healthcare devices such as wearables, diagnostic equipment, and implantable devices, which are linked to the internet and can communicate with one another. Blockchain (BC) technology can design a secure, decentralized system to store and share medical data in an IoMT-based intelligent healthcare system. Patient records were stored in a tamper-proof and decentralized way using BC, which provides high privacy and security for the patients. Furthermore, BC enables efficient and secure sharing of healthcare data between patients and health professionals, enhancing healthcare quality. Therefore, in this paper, we develop an IoMT with a blockchain-based smart healthcare system using encryption with an optimal deep learning (BSHS-EODL) model. The presented BSHS-EODL method allows BC-assisted secured image transmission and diagnoses models for the IoMT environment. The proposed method includes data classification, data collection, and image encryption. Initially, the IoMT devices enable data collection processes, and the gathered images are stored in BC for security. Then, image encryption is applied for data encryption, and its key generation method can be performed via the dingo optimization algorithm (DOA). Finally, the BSHS-EODL technique performs disease diagnosis comprising SqueezeNet, Bayesian optimization (BO) based parameter tuning, and voting extreme learning machine (VELM). A comprehensive set of simulation analyses on medical datasets highlights the betterment of the BSHS-EODL method over existing techniques with a maximum accuracy of 98.51%, whereas the existing methods such as DBN, YOLO-GC, ResNet, VGG-19, and CDNN models have lower accuracies of 94.15%, 94.24%, 96.19%, 91.19%, and 95.29% respectively.

show abstract

Section: Related Workmentioning

confidence: 99%

Internet of Medical Things with a Blockchain-Assisted Smart Healthcare System Using Metaheuristics with a Deep Learning Model

Albakri

Alqahtani

2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…A decentralized IoT data management strategy based on blockchain that Al-Karthik et al [14] suggested uses smart contracts to allow safe and open information sharing and authentication protocols. The authors used Hyperledger Fabric and Chaincode smart contracts to implement their proposed approach.…”

Section: Related Workmentioning

confidence: 99%

BlockGov: Blockchain-Based Data Governance in the Internet of Things using Smart Contracts

M. Rajkumar, N. S. Usha

2023

IJRITCC

View full text Add to dashboard Cite

The rapid growth and integration of the Internet of Things (IoT) emphasizes the crucial need for effective data governance. This research unveils a novel framework, capitalizing on blockchain and smart contracts, aimed at decentralizing data governance in the IoT sphere. Our approach allows stakeholders to formulate and enforce data governance collaboratively, ensuring a balance between transparency, adaptability, and flexibility. Using the Ethereum platform and Solidity as our smart contract language, we constructed a demonstrative proof-of-concept. Our comparative evaluations highlighted our system's superiority, outpacing previous works with a scalability score of 95%, flexibility at 90%, and an unmatched transparency score of 100%. This framework presents a transformative paradigm for organizations and individuals working with IoT data, offering an efficient, transparent, and robust data governance mechanism.

show abstract

“…Blockchain applications in waste management are examined by Jiang et al (2023) [166], who provide an overview, difficulties, and potential. In order to secure IoT-based healthcare multimedia data, Karthik et al (2023) [167] present deep intelligent blockchain technology, highlighting the deep learning and blockchain integration for improved security. This thorough synthesis advances our understanding of the opportunities and difficulties presented by the convergence of blockchain and IoT in a variety of fields.…”

mentioning

confidence: 99%

Exploring the Potential of Blockchain Technology in an IoT-Enabled Environment: A Review

Deepak,

Gulia,

Gill

et al. 2024

IEEE Access

View full text Add to dashboard Cite

Internet of Things (IoT) plays an essential contribution in connecting devices and enabling seamless data exchange, leading to increased efficiency and convenience. However, security concerns in IoT systems are significant, as compromised devices can lead to data breaches and privacy violations. Blockchain technology can enhance IoT security by providing decentralized consensus, immutability, and transparent transaction records, ensuring secure and trustworthy communication and data integrity. This review article gives a succinct but thorough understanding of blockchain technology, covering architecture of blockchain, working principles, types, applications, platforms, and its role in the IoT environment. The study highlights potential benefits of blockchain like enhanced security and privacy, and explores its integration with IoT. Additionally, the study discusses various real-world applications, examines blockchain platforms, and addresses the limitations and challenges associated with blockchain technology. This review serves as a valuable resource for researchers and practitioners seeking a deeper understanding of blockchain's potential and its implications in the IoT landscape.INDEX TERMS Blockchain, Data Exchange, Internet of Things (IoT), Privacy, Security.

show abstract

Deep intelligent blockchain technology for securing IoT-based healthcare multimedia data

Cited by 7 publications

References 34 publications

Internet of Medical Things with a Blockchain-Assisted Smart Healthcare System Using Metaheuristics with a Deep Learning Model

Internet of Medical Things with a Blockchain-Assisted Smart Healthcare System Using Metaheuristics with a Deep Learning Model

BlockGov: Blockchain-Based Data Governance in the Internet of Things using Smart Contracts

Exploring the Potential of Blockchain Technology in an IoT-Enabled Environment: A Review

Contact Info

Product

Resources

About