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Artificial Intelligence in Health Blockchain for health-care security

system, the involvement of third parties is not allowed SecNet is an architecture proposed by Wang et al.,
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in blockchain. Thus, health-care service maintained by combining actual big data with AI to enhance the
blockchain technology can only permit sharing of data robustness of cyber security. A large-scale Internet setting
contained within the blockchain architecture. The patients offers safe data storage, computation, and sharing. It
who use blockchain technology are facilitated with cost- primarily consists of three components. Blockchain-based
efficient data distribution. 39,44 Moreover, the patients are data sharing with ownership guarantees allows trusted
privileged with an extensive network for secure health- data exchange to create massive data in a large-scale
care systems, medical data exchange through blockchain, context. In addition, AI-based safe computing systems
health-care data protection, EHR facilities with attribute- come with more intelligent security rules, which aid in the
based cryptosystem, and facilities for monitoring clinical creation of more trustworthy cyberspace. Moreover, they
emergencies. There are four stages of securing clinical data purchase security services through trust value exchange,
in the health-care industry: a method for participants to receive financial rewards for
(i) First step: At first, various health-care data, including sharing their data or service, promoting data sharing, and
patient’s personal information and ID, are sent improving AI performance. Furthermore, the authors
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to the blockchain network through application describe a scenario of using conventional SecNet and its
programming interface (API). The current health IT potentially alternative deployment method and evaluate its
system tracks and stores all the data. 43 network security and economic revenue.
(ii) Second step: Blockchain technology has an internal
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transaction process through a smart contract. Entire Alqaralleh et al. developed a deep learning model for
transactions attached in the blockchain contain safe image transmission and diagnosis on the Internet
only patients’ public ID rather than their personal of Medical Things environment. Data gathering, secure
information. transactions, hash value encryption, and data classification
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(iii) Third step: A permanent ledger is connected with the are among the procedures included in the model. The
block. Thus, all sections become distinctly identifiable. elliptic curve cryptography (ECC) is used primarily, and
The API processes queries from the health provider the hybridization of the grasshopper with the fruit fly
in a reverse manner. The database of blocks stores optimization technique is used to generate the best ECC
anonymous patient data, e.g., gender, age, and illness. keys. The hash values are encrypted using the neighborhood
(iv) Fourth step: The patient will have a private key. The indexing sequence (NIS) with burrow wheeler transform
health-care provider can only access the patient’s (BWT) (NIS-BWT). Finally, a deep belief network is used
information after the patient shares the private key. in the categorization process to diagnose the presence of
The data stand is restricted to people who do not have disease. To identify the analysis of the optimal results of
a private key. the proposed model, substantial experimental validation
Hussein et al. proposed an extensive and prosperous is performed, and the results are examined from many
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system for handling the clinical record and information perspectives.
using blockchain technology. The method implements 6. Taxonomy of blockchain technology in
a different cryptographic technique for strong security
management of sensitive clinical data and adaptability of health care
the patients to simplified data access. Discrete wavelet Blockchain technology utilizes network technology with
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transform using hash function generation process was tamper-resistant data. In blockchain technology, current
employed to boost the strength and restrict the access of transactions cannot be changed. Instead, the transactions
data users. Moreover, genetic algorithms lower the time of can be updated using hash values. The taxonomy of
transaction nodes to enhance data reliability and designate blockchain technologies in health care is illustrated in
the data requests. Figure 4. Different features make blockchain technology
There are separate blocks in the blockchain network distinctive from others:
that is shaped by establishing chain events from the (i) Distributed ledger: In a distributed system, transactions
current block to the original block. After obtaining event are added to retrieve the system by removing failure
details, the block broadcasts into a network. Once the points.
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chain forms, the block is locked and cannot be reformed, (ii) Census mechanism: If every verified user of the network
updated, and deleted. Any exploitation of data handling grants a permission transaction, the transaction can
policies by users in the group will prompt data tracking be updated.
by data forensics team so as to secure and manage clinical (iii) Provenance: The entire data history is obtainable on
records. the blockchain network.

Volume 1 Issue 2 (2024) 36 doi: 10.36922/aih.2580