Proposing hierarchy-similarity based access control framework: A multilevel Electronic Health Record data sharing approach for interoperable environment

Bhartiya, Shalini; Mehrotra, Deepti; Girdhar, Anup

doi:10.1016/j.jksuci.2015.08.005

Cited by 10 publications

(6 citation statements)

References 15 publications

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“…Shalini Bhartiya [14] proposed an access control framework that applies hierarchy similarity analyser using XACML policies and these policy conflicts can be used in semantic, syntactic, temporal constraints in future scope.…”

Section: Related Workmentioning

confidence: 99%

A survey on health care data using Machine learning Algorithms

Manjulatha¹,

Pabboju²

2020

Preprint

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Big data in the healthcare has been growing rapidly in recent years. A massive amount of patient’s data is generated through various sources in this digitalized environment including wearable devices, mobile devices, electronic health records and medical centres. The medical data, which are exploding exponentially includes a large volume of structured and unstructured data. Patients information is shared and managed by many sources such as insurance, in the form of prescription, healthcare providers including the attackers which causes a severe security threats their confidential data. Cybercriminals use a variety of social engineering attacks like phishing, leakage of data, embedding virus and trojan horse into the attachments, DNS snooping, sniffing, and many more. In this paper a brief overview is done on different data mining and security techniques which are implemented in healthcare data. The study and its presentation in this context would be helpful in not only analysing but also predicting chronic diseases depending upon the available stored data which has been collected from various sources in the area of medical expert system.

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Section: Related Workmentioning

confidence: 99%

A survey on health care data using Machine learning Algorithms

Manjulatha¹,

Pabboju²

2020

Preprint

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“…It includes over 2000 data sets from 70 major and typically definitive data agencies. This includes the official details of licensed premises provided by the Victorian Commission for Gambling and Liquor Regulation (VCGLR) 4 . As shown in Figure 8, a typical scenario can be depicted where the Zip codes of both data sets facilitates the data linkage of T1DM and locations of bottleshops.…”

Section: Case Study-privacy Protection On Linkage Aurin and Addnmentioning

confidence: 99%

“…The international standard, XACML (eXtensible Access Control Markup Language) includes common request/response protocols and associated policy components to support authorisation [1]. Due to its standardisation, widespread adoption and rich expressiveness, XACML has been widely implemented in EHR systems [2] [3] [4]. In particular, the obligation component of XACML has the potential to seamlessly introduce other policies (e.g.…”

Section: Introductionmentioning

confidence: 99%

Semantic-Based Privacy Protection of Electronic Health Records for Collaborative Research

Lü

Sinnott

2016

2016 IEEE Trustcom/BigDataSE/Ispa

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Combined health information and web-based technologies can be used to support healthcare and research activities associated with electronic health records (EHRs).EHRs used for research purposes demand privacy, confidentiality and all information governance concerns are addressed. However, existing solutions are unable to meet the evolving research needs especially when supporting data access and linkage across organization boundaries. In this work, we show how semantic methods can aid in the specification and enforcement of policies for privacy protection. This is illustrated through a case study associated with the Australasian Diabetes Data Network (ADDN), the national paediatric type-1 diabetes data registry and the Australian Urban Research Infrastructure Network (AURIN) platform that supports Australia-wide access to urban and built environment data sets. Specifically we show that through extending the eXtensible Access Control Markup Language (XACML) with semantic capabilities, we are able to support fine-grained privacy-preserving policies leveraging semantic reasoning that is not directly available in XACML or other existing security policy specification languages.

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“…Sin embargo, al existir una falta de consideración con respecto a la privacidad de la identidad de los propietarios de registros médicos electrónicos, se pueden utilizar técnicas de anonimización para garantizar la privacidad de la identidad de los usuarios. Existen algunos esquemas ABE anónimos que abordan no solo la privacidad de los datos sino también la privacidad de la identidad; por ende, aquellos esquemas proporcionan un análisis de confidencialidad, anonimato y flexibilidad [76].…”

Section: Introductionunclassified

Modelos de control de acceso más utilizados en la seguridad de datos médicos

Campos-Montero,

Rodríguez-Sandoval,

Mendoza de los Santos

2023

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El acceso no autorizado a datos sensibles de pacientes es un problema que atenta contra ellos mismos y la seguridad de las organizaciones dedicadas al servicio de salud, para lo cual es fundamental implementar controles de acceso (CA), los cuales deben impedir el acceso y uso malintencionado de los datos, por ese motivo se hizo una investigación basada en revisión sistemática, utilizando como metodología a Prisma; además, se utilizó SCOPUS como base de datos incluyendo 82 artículos, que sirvieron para encontrar los modelos de control de acceso más utilizados; por consiguiente, se identificó 5 modelos que fueron los más utilizados (ABE, ABAC, RBAC, BBAC y MAC), representando un total del 52% de todos los estudios revisados, mientras que un 29% pertenecía a los que se implementaron una única vez y el 19% restante a las que surgieron por la solución de problemas identificados dentro de los 5 modelos de uso frecuente.

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Proposing hierarchy-similarity based access control framework: A multilevel Electronic Health Record data sharing approach for interoperable environment

Cited by 10 publications

References 15 publications

A survey on health care data using Machine learning Algorithms

A survey on health care data using Machine learning Algorithms

Semantic-Based Privacy Protection of Electronic Health Records for Collaborative Research

Modelos de control de acceso más utilizados en la seguridad de datos médicos

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