PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems

PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems

In IoT-based healthcare, medical devices are more vulnerable to numerous security threats and attacks than other network devices. Current solutions are able to provide protection to patients’ data during data transmission to some extent, but cannot prevent some sophisticated threats and attacks suc...

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Main Authors: Luo, Entao, Bhuiyan, Md Zakirul Alam, Wang, Guojun, Rahman, Md. Arafatur, Wu, Jie, Atiquzzaman, Mohammed
Format: Article
Language:English
Published: IEEE Communications Society 2018
Subjects:
Q Science (General)
Online Access:http://umpir.ump.edu.my/id/eprint/23751/
http://umpir.ump.edu.my/id/eprint/23751/
http://umpir.ump.edu.my/id/eprint/23751/
http://umpir.ump.edu.my/id/eprint/23751/1/PrivacyProtector.pdf
id ump-23751
recordtype eprints
spelling ump-237512019-01-22T02:55:05Z http://umpir.ump.edu.my/id/eprint/23751/ PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems Luo, Entao Bhuiyan, Md Zakirul Alam Wang, Guojun Rahman, Md. Arafatur Wu, Jie Atiquzzaman, Mohammed Q Science (General) In IoT-based healthcare, medical devices are more vulnerable to numerous security threats and attacks than other network devices. Current solutions are able to provide protection to patients’ data during data transmission to some extent, but cannot prevent some sophisticated threats and attacks such as collusion attacks and data leakage. In this article, we first investigate the challenges,with privacy protected data collection. Then we propose a practical framework called PrivacyProtector, patient privacy protected data collection, with the objective of preventing these types of attacks. PrivacyProtector includes the ideas of secret sharing and share repairing (in case of data loss or compromise) for patients’ data privacy. Since it is the first time, we apply the Slepian-Wolf-coding-based secret sharing (SW-SSS) in PrivacyProtector. In the framework, we use a distributed database consisting of multiple cloud servers, which ensures that the privacy of patients’ personal data can remain protected as long as one of the servers remains uncompromised. We also present a patient access control scheme in which multiple cloud servers collaborate in shared construction to offer patients’ data to healthcare providers without revealing the content of the data. The privacy performance analysis has shown that the PrivacyProtector framework is secure and privacy-protected against various attacks. IEEE Communications Society 2018 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/23751/1/PrivacyProtector.pdf Luo, Entao and Bhuiyan, Md Zakirul Alam and Wang, Guojun and Rahman, Md. Arafatur and Wu, Jie and Atiquzzaman, Mohammed (2018) PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems. IEEE Communications Magazine, 5 (2). pp. 163-168. ISSN 0163-6804 https://doi.org/10.1109/MCOM.2018.1700364 https://doi.org/10.1109/MCOM.2018.1700364
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic Q Science (General)
spellingShingle Q Science (General)
Luo, Entao
Bhuiyan, Md Zakirul Alam
Wang, Guojun
Rahman, Md. Arafatur
Wu, Jie
Atiquzzaman, Mohammed
PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems
description In IoT-based healthcare, medical devices are more vulnerable to numerous security threats and attacks than other network devices. Current solutions are able to provide protection to patients’ data during data transmission to some extent, but cannot prevent some sophisticated threats and attacks such as collusion attacks and data leakage. In this article, we first investigate the challenges,with privacy protected data collection. Then we propose a practical framework called PrivacyProtector, patient privacy protected data collection, with the objective of preventing these types of attacks. PrivacyProtector includes the ideas of secret sharing and share repairing (in case of data loss or compromise) for patients’ data privacy. Since it is the first time, we apply the Slepian-Wolf-coding-based secret sharing (SW-SSS) in PrivacyProtector. In the framework, we use a distributed database consisting of multiple cloud servers, which ensures that the privacy of patients’ personal data can remain protected as long as one of the servers remains uncompromised. We also present a patient access control scheme in which multiple cloud servers collaborate in shared construction to offer patients’ data to healthcare providers without revealing the content of the data. The privacy performance analysis has shown that the PrivacyProtector framework is secure and privacy-protected against various attacks.
format Article
author Luo, Entao
Bhuiyan, Md Zakirul Alam
Wang, Guojun
Rahman, Md. Arafatur
Wu, Jie
Atiquzzaman, Mohammed
author_facet Luo, Entao
Bhuiyan, Md Zakirul Alam
Wang, Guojun
Rahman, Md. Arafatur
Wu, Jie
Atiquzzaman, Mohammed
author_sort Luo, Entao
title PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems
title_short PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems
title_full PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems
title_fullStr PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems
title_full_unstemmed PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems
title_sort privacyprotector: privacy-protected patient data collection in iot-based healthcare systems
publisher IEEE Communications Society
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/23751/
http://umpir.ump.edu.my/id/eprint/23751/
http://umpir.ump.edu.my/id/eprint/23751/
http://umpir.ump.edu.my/id/eprint/23751/1/PrivacyProtector.pdf
first_indexed 2023-09-18T22:35:42Z
last_indexed 2023-09-18T22:35:42Z
_version_ 1777416580861263872

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