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<p>Sensitive healthcare data stored in the cloud is increasingly vulnerable to privacy breaches and unauthorized access due to limitations in traditional security mechanisms. Existing approaches often rely on centralized systems and isolated cryptographic techniques, which lack transparency, scalability, and resistance to advanced attacks. To address these challenges, this paper presents a novel decentralized privacy preservation scheme leveraging blockchain technology to enhance healthcare data security in the cloud. The proposed framework integrates the Edward Curve Digital Signature Algorithm (EdDSA) with the SHA-256 hashing function to ensure data integrity and authenticity. For secure data encryption, a Modified Menezes-Vanstone based Elliptic Curve ElGamal Encryption Scheme (MMV-ECE) is introduced, offering lightweight yet robust protection. Encrypted data is stored using the InterPlanetary File System (IPFS) for decentralized and scalable off-chain storage, while only cryptographic hashes are retained on-chain. A smart contract mechanism developed via Remix-Ethereum enforces access control policies, and a novel Exponentially Affinity propagated Delegated Proof of Stake (AEP-DPoS) consensus algorithm is proposed to improve transaction validation efficiency. The system is evaluated using the Cleveland Heart Disease dataset and validated through performance metrics such as encryption time, decryption time, key generation time, throughput, and latency. The results demonstrate that the proposed model significantly outperforms conventional approaches like RSA, AES, and ECC. Specifically, the encryption, decryption, and key generation times were reduced to 0.035&#xa0;s, 0.167&#xa0;s, and 0.463&#xa0;s, respectively. The AEP-DPoS mechanism achieved a high throughput of 70.95 transactions per second and a low latency of 42.52&#xa0;s. These findings confirm the system’s effectiveness in providing secure, efficient, and scalable healthcare data management in decentralized cloud environments.</p>

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A decentralized blockchain based privacy preservation scheme for healthcare data security enhancement in cloud

  • 期刊论文

  • 发表日期：

    2025年8月19日

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  • Narendra Kumar,
  • Sunil Kumar,
  • Rajeev Kumar Sharma,
  • Rupak Sharma,
  • Kapil Tomar

摘要

Sensitive healthcare data stored in the cloud is increasingly vulnerable to privacy breaches and unauthorized access due to limitations in traditional security mechanisms. Existing approaches often rely on centralized systems and isolated cryptographic techniques, which lack transparency, scalability, and resistance to advanced attacks. To address these challenges, this paper presents a novel decentralized privacy preservation scheme leveraging blockchain technology to enhance healthcare data security in the cloud. The proposed framework integrates the Edward Curve Digital Signature Algorithm (EdDSA) with the SHA-256 hashing function to ensure data integrity and authenticity. For secure data encryption, a Modified Menezes-Vanstone based Elliptic Curve ElGamal Encryption Scheme (MMV-ECE) is introduced, offering lightweight yet robust protection. Encrypted data is stored using the InterPlanetary File System (IPFS) for decentralized and scalable off-chain storage, while only cryptographic hashes are retained on-chain. A smart contract mechanism developed via Remix-Ethereum enforces access control policies, and a novel Exponentially Affinity propagated Delegated Proof of Stake (AEP-DPoS) consensus algorithm is proposed to improve transaction validation efficiency. The system is evaluated using the Cleveland Heart Disease dataset and validated through performance metrics such as encryption time, decryption time, key generation time, throughput, and latency. The results demonstrate that the proposed model significantly outperforms conventional approaches like RSA, AES, and ECC. Specifically, the encryption, decryption, and key generation times were reduced to 0.035 s, 0.167 s, and 0.463 s, respectively. The AEP-DPoS mechanism achieved a high throughput of 70.95 transactions per second and a low latency of 42.52 s. These findings confirm the system’s effectiveness in providing secure, efficient, and scalable healthcare data management in decentralized cloud environments.