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JCR Impact Factor: 0.699
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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LATEST NEWS

2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

Read More »


    
 

  2/2017 - 5

Hybrid Solution for Privacy-Preserving Access Control for Healthcare Data

SMITHAMOL, M. B., RAJESWARI, S. See more information about RAJESWARI, S. on SCOPUS See more information about RAJESWARI, S. on SCOPUS See more information about RAJESWARI, S. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,342 KB) | Citation | Downloads: 384 | Views: 671

Author keywords
data privacy, electronic medical records, internet of things, cloud, access control

References keywords
encryption(11), cloud(10), attribute(9), security(7), secure(7), data(7), control(6), privacy(5), policy(5), grained(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-05-31
Volume 17, Issue 2, Year 2017, On page(s): 31 - 38
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.02005
Web of Science Accession Number: 000405378100005
SCOPUS ID: 85020138510

Abstract
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The booming in cloud and IoT technologies has accelerated the growth of healthcare system. The IoT devices monitor the patient's health, and upload collected data as Electronic Medical Records (EMRs) to the cloud for storage and sharing. Outsourcing EMRs to the cloud introduce new security and privacy challenges. In this paper, we proposed a novel architecture ensuring security and privacy for the outsourced health records. The proposed model uses partially ordered set (POSET) for constructing the group based access structure and Ciphertext-Policy Attribute-Based Encryption (CP-ABE) to provide fine-grained EMR access control. The modified group based CP-ABE (G-CP-ABE) minimizes the computational overhead by reducing the number of leaf nodes in the access tree. Also, the proposed G-CP-ABE framework merges symmetric encryption and CP-ABE scheme to minimize the overall encryption time. As a result, G-CP-ABE can be used to monitor health conditions even from a resource constrained IoT device. The performance analysis shows the efficiency of the proposed model, making it suitable for practical use.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 1,897 TCR
SCOPUS® Citations for all references: 9,190 TCR

Web of Science® Average Citations per reference: 59 ACR
SCOPUS® Average Citations per reference: 287 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-09-20 07:56 in 195 seconds.




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