期刊
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
卷 6, 期 1, 页码 6-15出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TETCI.2020.2993841
关键词
Privacy; Biomedical monitoring; Artificial intelligence; Encryption; Hospitals; Artificial intelligence; smart healthcare; security; privacy; block design; human-in-the-loop
资金
- National Natural Science Foundation of China [U1836115, 61672295, 61922045]
- Natural Science Foundation of Jiangsu Province [BK20181408]
- Peng Cheng Laboratory Project of Guangdong Province [PCL2018KP004]
- Opening Project of Shanghai Trusted Industrial Control Platform [TICPSH202003011-ZC]
- Postgraduate Research& Practice Innovation Program of Jiangsu Province [SJKY19_0975]
- CICAEET Fund
- PAPD Fund
This paper focuses on designing a human-in-the-loop-aided scheme to preserve privacy in smart healthcare. The proposed scheme utilizes block design technique to obfuscate health indicators and introduces human-in-the-loop access for privacy protection.
Nowadays, artificial intelligence (AI) has become the core technology for numerous application fields ranging from self-driving cars to smart cities. Smart healthcare, as an important part of smart cities, constitutes one of the most essential pillars of social and economic stability. Despite all the possibilities offered by smart healthcare, how to handle the dark aspects of smart healthcare such as security, privacy and trust issues, and so on remains unsolved. In this paper, we focus on designing a human-in-the-loop-aided (HitL-aided) scheme to preserve privacy in smart healthcare. On the one hand, a block design technique is employed to obfuscate various health indicators from the hospitals and the smart wearable devices. On the other hand, human-in-the-loop (HitL) is introduced to enable a privacy access of the health reports from the smart healthcare platform. In addition, the performance analysis and case study indicate that the proposed HitL-aided scheme is effective in preserving privacy for smart healthcare.
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