Blockchain-Based Modified AES with Chaotic Random Key Generation for Secured E-Medical Data Sharing

The Electronic Medical Documentations have gained vitality and are stated as the pillar of digital healthcare. It is the main platform to store and retrieve the information of patients. It possesses numerous benefits like cost minimization, few medical errors with better healthcare access and tracking. Though the advantages and adoption of EMD have been extensively stated, the challenges entangled with their usage persist, particularly with the safety and integrity of the patient’s data that are stored in the cloud. Conventional data sharing methods have been centralized and encountered problems of sole point-of-failure. Thus, a decentralized system is required where the blockchain concept comes into play. Moreover, protecting personal details from unauthorized entrée by guaranteeing data integrity is vital where cryptography gains its significance. Though traditional methods have used algorithms based on these concepts for secured EMD sharing, they lacked with regard for privacy and security. To rectify this problem, the objective of the present study proposes Modified-Advanced Encryption Standard based on the chaos random key generation. In a traditional AES system, a static key finds applicability which must be swapped in advance and assured to be maintained safely. Nevertheless, in the proposed model, a chaotic system’s synchronization technology is introduced wherein the static key turns random and dynamic which avoids the need to be maintained or transferred in any open channels. Besides, a Modified Digest hashing algorithm is also used with M-AES for feeding the encrypted text and hash into data blocks. Performance of the proposed merging technique encompassing a hybrid pattern from both patient ID and medical records is assessed about significant metrics for determining its efficiency. The overall model performance are estimated using various estimation parameters such as the execution time, decryption time, encryption time, memory consumption and usage rates and the time required for key generation. Findings of the proposed work deliberates that higher level of security are ensured, whereby a long-term protection are used, which intends to prevents adversaries from gaining a static target for prolonged attacks. Additionally, the security level of the proposed system performs better in terms of integrity, privacy, authentication, access control, and cryptographic function.

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Publication Details

Journal
CLEI electronic journal
Published
2025-04-06
DOI
https://doi.org/10.19153/cleiej.28.2.14
Citations
1
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.84
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article

Blockchain-Based Modified AES with Chaotic Random Key Generation for Secured E-Medical Data Sharing

Shri Ram, M Vinothkumar
1 citations
CLEI electronic journal
Brain Tumor Detection and Classification
0.84
article

Blockchain-Based Modified AES with Chaotic Random Key Generation for Secured E-Medical Data Sharing

Shri Ram, M Vinothkumar
article en
1 citations

Abstract

The Electronic Medical Documentations have gained vitality and are stated as the pillar of digital healthcare. It is the main platform to store and retrieve the information of patients. It possesses numerous benefits like cost minimization, few medical errors with better healthcare access and tracking. Though the advantages and adoption of EMD have been extensively stated, the challenges entangled with their usage persist, particularly with the safety and integrity of the patient’s data that are stored in the cloud. Conventional data sharing methods have been centralized and encountered problems of sole point-of-failure. Thus, a decentralized system is required where the blockchain concept comes into play. Moreover, protecting personal details from unauthorized entrée by guaranteeing data integrity is vital where cryptography gains its significance. Though traditional methods have used algorithms based on these concepts for secured EMD sharing, they lacked with regard for privacy and security. To rectify this problem, the objective of the present study proposes Modified-Advanced Encryption Standard based on the chaos random key generation. In a traditional AES system, a static key finds applicability which must be swapped in advance and assured to be maintained safely. Nevertheless, in the proposed model, a chaotic system’s synchronization technology is introduced wherein the static key turns random and dynamic which avoids the need to be maintained or transferred in any open channels. Besides, a Modified Digest hashing algorithm is also used with M-AES for feeding the encrypted text and hash into data blocks. Performance of the proposed merging technique encompassing a hybrid pattern from both patient ID and medical records is assessed about significant metrics for determining its efficiency. The overall model performance are estimated using various estimation parameters such as the execution time, decryption time, encryption time, memory consumption and usage rates and the time required for key generation. Findings of the proposed work deliberates that higher level of security are ensured, whereby a long-term protection are used, which intends to prevents adversaries from gaining a static target for prolonged attacks. Additionally, the security level of the proposed system performs better in terms of integrity, privacy, authentication, access control, and cryptographic function.

CLEI electronic journalVol. 28(2)
Anna University, Chennai (IN)
Openalex Percentile: Top 26%
Brain Tumor Detection and Classification
0.84
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