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A practical application of CP-ABE for mobile PHR system: a study on the user accountability

Overview of attention for article published in SpringerPlus, August 2016
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Title
A practical application of CP-ABE for mobile PHR system: a study on the user accountability
Published in
SpringerPlus, August 2016
DOI 10.1186/s40064-016-3002-y
Pubmed ID
Authors

Hanshu Hong, Di Chen, Zhixin Sun

Abstract

Attribute based encryption has been widely applied for secure data protection in PHR systems. However, since different users may share the same attributes in the system, a user may leaks his private key for illegal data sharing without being detected. This will add more threat to the private data stored in PHR system. To help users achieve higher efficiency and more secure data sharing in mobile PHR system, based on previous works, we study the traitor tracing mechanism in attribute based cryptosystem and propose a high efficient attribute based encryption with user accountability in mobile PHR system. If a malicious PHR user exposes his private key for illegal data sharing, his identity can be accurately pinpointed by the system manager. During the whole process of data sharing, no bilinear pairing operations are needed, hence this will the mobile terminal devices from heavy computation burden. As a further study, in this short report, we show that using a novel attribute based encryption with user accountability can help users achieve better efficiency and more secure data sharing in mobile PHR system.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 30%
Student > Master 3 30%
Other 1 10%
Researcher 1 10%
Unknown 2 20%
Readers by discipline Count As %
Computer Science 3 30%
Social Sciences 2 20%
Business, Management and Accounting 1 10%
Nursing and Health Professions 1 10%
Unknown 3 30%