Distributed and Decentralized Attribute Based Access Control for Smart Health Care Data

Author(s):  
B. Ravinder Reddy ◽  
T. Adilakshmi
2018 ◽  
Vol 7 (4.10) ◽  
pp. 504
Author(s):  
K. Kavitha ◽  
D. Anuradha ◽  
P. Pandian

Huge amount of health care data are available online to improve the overall performance of health care system. Since this huge health care Big-data is valuable and sensitive, it requires safety. In this paper we analyze numerous ways in which the health care Big-data can be protected. In recent days many augmented security algorithm that are suitable for Big-data have emerged like, El-Gamal, Triple-DES, and Homomorphic algorithms. Also authentication and access control can be implemented over Big-data using Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) schemes.Along with security to Big-data we try to evolve the ways in which the valuable Big-data can be optimized to improve the Big-data analysis. Mathematical optimization techniques such as simple and multi-purpose optimization and simulation are employed in Big-data to maximize the patient satisfaction and usage of doctor’s consulting facility. And also, to minimize the cost spent by patient and energy wasted.  


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tanvi Garg ◽  
Navid Kagalwalla ◽  
Shubha Puthran ◽  
Prathamesh Churi ◽  
Ambika Pawar

Purpose This paper aims to design a secure and seamless system that ensures quick sharing of health-care data to improve the privacy of sensitive health-care data, the efficiency of health-care infrastructure, effective treatment given to patients and encourage the development of new health-care technologies by researchers. These objectives are achieved through the proposed system, a “privacy-aware data tagging system using role-based access control for health-care data.” Design/methodology/approach Health-care data must be stored and shared in such a manner that the privacy of the patient is maintained. The method proposed, uses data tags to classify health-care data into various color codes which signify the sensitivity of data. It makes use of the ARX tool to anonymize raw health-care data and uses role-based access control as a means of ensuring only authenticated persons can access the data. Findings The system integrates the tagging and anonymizing of health-care data coupled with robust access control policies into one architecture. The paper discusses the proposed architecture, describes the algorithm used to tag health-care data, analyzes the metrics of the anonymized data against various attacks and devises a mathematical model for role-based access control. Originality/value The paper integrates three disparate topics – data tagging, anonymization and role-based access policies into one seamless architecture. Codifying health-care data into different tags based on International Classification of Diseases 10th Revision (ICD-10) codes and applying varying levels of anonymization for each data tag along with role-based access policies is unique to the system and also ensures the usability of data for research.


2021 ◽  
Author(s):  
Sana Imtiaz ◽  
Muhammad Arsalan ◽  
Vladimir Vlassov ◽  
Ramin Sadre

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