A survey on blockchain security for electronic health record

IF 3 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Multimedia Tools and Applications Pub Date : 2024-09-09 DOI:10.1007/s11042-024-19883-5
Chandini A G, P. I Basarkod
{"title":"A survey on blockchain security for electronic health record","authors":"Chandini A G, P. I Basarkod","doi":"10.1007/s11042-024-19883-5","DOIUrl":null,"url":null,"abstract":"<p>Numerous healthcare organizations maintain track of the patients’ medical information with an Electronic Health Record (EHR). Nowadays, patients demand instant access to their medical records. Hence, Deep Learning (DL) methods are employed in electronic healthcare sectors for medical image processing and smart supply chain management. Various approaches are presented for the protection of healthcare data of patients using blockchain however, there are concerns regarding the security and privacy of patient medical records in the health industry, where data can be accessed instantly. The blockchain-based security with DL approaches helps to solve this problem and there is a need for improvements on the DL-based blockchain methods for privacy and security of patient data and access control strategies with developments in the supply chain. The survey provides a clear idea of DL-based strategies used in electronic healthcare data storage and security along with the integrity verification approaches. Also, it provides a comparative analysis to demonstrate the effectiveness of various blockchain-based EHR handling techniques. Moreover, future directions are provided to overcome the existing impact of various techniques in blockchain security for EHRs.</p>","PeriodicalId":18770,"journal":{"name":"Multimedia Tools and Applications","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multimedia Tools and Applications","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s11042-024-19883-5","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Numerous healthcare organizations maintain track of the patients’ medical information with an Electronic Health Record (EHR). Nowadays, patients demand instant access to their medical records. Hence, Deep Learning (DL) methods are employed in electronic healthcare sectors for medical image processing and smart supply chain management. Various approaches are presented for the protection of healthcare data of patients using blockchain however, there are concerns regarding the security and privacy of patient medical records in the health industry, where data can be accessed instantly. The blockchain-based security with DL approaches helps to solve this problem and there is a need for improvements on the DL-based blockchain methods for privacy and security of patient data and access control strategies with developments in the supply chain. The survey provides a clear idea of DL-based strategies used in electronic healthcare data storage and security along with the integrity verification approaches. Also, it provides a comparative analysis to demonstrate the effectiveness of various blockchain-based EHR handling techniques. Moreover, future directions are provided to overcome the existing impact of various techniques in blockchain security for EHRs.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
关于电子健康记录区块链安全性的调查
许多医疗机构通过电子病历(EHR)追踪病人的医疗信息。如今,患者要求即时访问他们的医疗记录。因此,深度学习(DL)方法被用于电子医疗保健领域的医学图像处理和智能供应链管理。使用区块链保护患者医疗数据的方法多种多样,但在可以即时访问数据的医疗行业中,患者医疗记录的安全性和隐私性令人担忧。基于 DL 方法的区块链安全有助于解决这一问题,随着供应链的发展,有必要改进基于 DL 的区块链方法,以确保患者数据的隐私和安全以及访问控制策略。调查清楚地说明了电子医疗数据存储和安全中使用的基于 DL 的策略以及完整性验证方法。此外,它还提供了对比分析,以证明各种基于区块链的电子病历处理技术的有效性。此外,还提供了未来发展方向,以克服区块链安全技术对电子病历的现有影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Multimedia Tools and Applications
Multimedia Tools and Applications 工程技术-工程:电子与电气
CiteScore
7.20
自引率
16.70%
发文量
2439
审稿时长
9.2 months
期刊介绍: Multimedia Tools and Applications publishes original research articles on multimedia development and system support tools as well as case studies of multimedia applications. It also features experimental and survey articles. The journal is intended for academics, practitioners, scientists and engineers who are involved in multimedia system research, design and applications. All papers are peer reviewed. Specific areas of interest include: - Multimedia Tools: - Multimedia Applications: - Prototype multimedia systems and platforms
期刊最新文献
MeVs-deep CNN: optimized deep learning model for efficient lung cancer classification Text-driven clothed human image synthesis with 3D human model estimation for assistance in shopping Hybrid golden jackal fusion based recommendation system for spatio-temporal transportation's optimal traffic congestion and road condition classification Deep-Dixon: Deep-Learning frameworks for fusion of MR T1 images for fat and water extraction Unified pre-training with pseudo infrared images for visible-infrared person re-identification
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1