Enhancing privacy in IoT-based healthcare using provable partitioned secure blockchain principle and encryption

利用可证明的分区安全区块链原理和加密技术增强基于物联网的医疗保健领域的隐私保护

阅读:1

Abstract

The Internet of Things (IoT) has attained significant interest recently, particularly in the medical field due to the quick development of IoT devices. Medical related data contains a significant volume of personal information, and it is crucial to maintain privacy. As medical information becomes increasingly electronic in the era of big data, securely and accurately storing medical information is critical. However, the heterogeneity of information systems poses a significant challenge to their sharing. Moreover, medical data typically comprises sensitive information, and sharing it can potentially lead to breaches of personal privacy. Data sharing is a significant concern in healthcare because of privacy leakage and security issues. To combat this issue, this paper introduces the prediction and Provable Partitioned Secure Block Chain Principle (PPSBCP) technique is used to secure healthcare data sharing. Initially, in the healthcare data analysis phase, the Preprocessing and normalization are carried out by Z-score normalized for analysing the healthcare-sensitive margins. The SSIR (Sensitive Spectral Impact Rate) method is applied to find the sensitive records. Based on the impact margins, the Binomial Quadratic Sensitive Data Prediction (BQSDP) method is applied to categorize the sensitive and non-sensitive information. In the blockchain phase, create a Hash Index Policy (HIP) to encrypt the data using a Foldable Blockchain Encryption Standard (FBES). The Master Node Handover Authentication Policy (MNHAP) is applied to verify the private key in the data safety. The Distributed Hyper Ledger Mechanism (DHLM) is applied to make the chain transaction principle. The proposed system accomplishes high performance in security by achieving the parameters in verification and validation as well as compared to the existing systems.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。