Lightweight and privacy-aware fine-grained access control for IoT-oriented smart health

With the booming of Internet of Things (IoT), smart health (s-health) is becoming an emerging and attractive paradigm. It can provide an accurate prediction of various diseases and improve the quality of healthcare. Nevertheless, data security and user privacy concerns still remain issues to be addr...

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Main Authors: SUN, Jianfei, XIONG, Hu, LIU, Ximeng, ZHANG, Yinghui, NIE, Xuyun, DENG, Robert H.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2020
Subjects:
IoT
Online Access:https://ink.library.smu.edu.sg/sis_research/5301
https://ink.library.smu.edu.sg/context/sis_research/article/6304/viewcontent/Lightweight_Privacy_Aware_SmartHealth_av.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-63042020-10-08T05:25:37Z Lightweight and privacy-aware fine-grained access control for IoT-oriented smart health SUN, Jianfei XIONG, Hu LIU, Ximeng ZHANG, Yinghui NIE, Xuyun DENG, Robert H. With the booming of Internet of Things (IoT), smart health (s-health) is becoming an emerging and attractive paradigm. It can provide an accurate prediction of various diseases and improve the quality of healthcare. Nevertheless, data security and user privacy concerns still remain issues to be addressed. As a high potential and prospective solution to secure IoT-oriented s-health applications, ciphertext policy attribute-based encryption (CP-ABE) schemes raise challenges, such as heavy overhead and attribute privacy of the end users. To resolve these drawbacks, an optimized vector transformation approach is first proposed to efficiently transform the access policy and user attribute set into respective vectors of shorter length while other approaches result in redundant and longer vectors. Our transformation approach can greatly relieve the costly overheard of key generation, encryption, and decryption phases. Then, based on the transformation approach and the offline/online computation technology, we propose a lightweight policy-hiding CP-ABE scheme for the IoT-oriented s-health application. With our proposed scheme, data users in the s-health system can perform lightweight encryption and decryption without leaking any sensitive privacy about the attributes of the user. Finally, the formal security analysis, the theoretic performance evaluation and experiment results indicate that the solution is secure and efficient. 2020-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5301 info:doi/10.1109/JIOT.2020.2974257 https://ink.library.smu.edu.sg/context/sis_research/article/6304/viewcontent/Lightweight_Privacy_Aware_SmartHealth_av.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Medical services Encryption Privacy Access control Data privacy Internet of Things IoT policy hiding privacy aware smart health Health Information Technology Information Security
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Medical services
Encryption
Privacy
Access control
Data privacy
Internet of Things
IoT
policy hiding
privacy aware
smart health
Health Information Technology
Information Security
spellingShingle Medical services
Encryption
Privacy
Access control
Data privacy
Internet of Things
IoT
policy hiding
privacy aware
smart health
Health Information Technology
Information Security
SUN, Jianfei
XIONG, Hu
LIU, Ximeng
ZHANG, Yinghui
NIE, Xuyun
DENG, Robert H.
Lightweight and privacy-aware fine-grained access control for IoT-oriented smart health
description With the booming of Internet of Things (IoT), smart health (s-health) is becoming an emerging and attractive paradigm. It can provide an accurate prediction of various diseases and improve the quality of healthcare. Nevertheless, data security and user privacy concerns still remain issues to be addressed. As a high potential and prospective solution to secure IoT-oriented s-health applications, ciphertext policy attribute-based encryption (CP-ABE) schemes raise challenges, such as heavy overhead and attribute privacy of the end users. To resolve these drawbacks, an optimized vector transformation approach is first proposed to efficiently transform the access policy and user attribute set into respective vectors of shorter length while other approaches result in redundant and longer vectors. Our transformation approach can greatly relieve the costly overheard of key generation, encryption, and decryption phases. Then, based on the transformation approach and the offline/online computation technology, we propose a lightweight policy-hiding CP-ABE scheme for the IoT-oriented s-health application. With our proposed scheme, data users in the s-health system can perform lightweight encryption and decryption without leaking any sensitive privacy about the attributes of the user. Finally, the formal security analysis, the theoretic performance evaluation and experiment results indicate that the solution is secure and efficient.
format text
author SUN, Jianfei
XIONG, Hu
LIU, Ximeng
ZHANG, Yinghui
NIE, Xuyun
DENG, Robert H.
author_facet SUN, Jianfei
XIONG, Hu
LIU, Ximeng
ZHANG, Yinghui
NIE, Xuyun
DENG, Robert H.
author_sort SUN, Jianfei
title Lightweight and privacy-aware fine-grained access control for IoT-oriented smart health
title_short Lightweight and privacy-aware fine-grained access control for IoT-oriented smart health
title_full Lightweight and privacy-aware fine-grained access control for IoT-oriented smart health
title_fullStr Lightweight and privacy-aware fine-grained access control for IoT-oriented smart health
title_full_unstemmed Lightweight and privacy-aware fine-grained access control for IoT-oriented smart health
title_sort lightweight and privacy-aware fine-grained access control for iot-oriented smart health
publisher Institutional Knowledge at Singapore Management University
publishDate 2020
url https://ink.library.smu.edu.sg/sis_research/5301
https://ink.library.smu.edu.sg/context/sis_research/article/6304/viewcontent/Lightweight_Privacy_Aware_SmartHealth_av.pdf
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