Paper Info
Title
An Efficient and Privacy-Preserving <tex>$k$</tex>-NN Query Scheme for eHealthcare Data
Abstract
As eHealthcare data is very sensitive yet cloud servers are not fully trustable today, many security, privacy and efficiency challenges will arise when cloud meets eHealthcare data. In this paper, aiming at addressing the privacy and efficiency challenges, we present an efficient and privacy-preserving <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$k$</tex> Nearest Neighbour ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$k$</tex> -NN) query scheme for encrypted eHealthcare data in cloud. The proposed scheme is characterized by integrating kd-tree and homomorphic encryption techniques for efficient storing encrypted data in cloud and privacy-preserving <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$k$</tex> -NN query over encrypted data. Detailed security analysis shows that our proposed scheme is really privacy preserving under our security model. In addition, performance evaluation also indicates that our proposed scheme is efficient in terms of computational complexity.
Year
DOI
Venue
2018
10.1109/Cybermatics_2018.2018.00088
2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
Keywords
Field
DocType
Cloud computing,Medical services,Data models,Encryption,Computational modeling
Homomorphic encryption,Data modeling,Nearest neighbour,Computer science,Encryption,Theoretical computer science,Security analysis,Computer security model,Computational complexity theory,Cloud computing
Conference
ISBN
Citations 
PageRank 
978-1-5386-7975-3
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Yandong Zheng1206.38
Rongxing Lu25091301.87