Journal
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 17, Issue 1, Pages 514-523Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2018.2883680
Keywords
Cloud computing; efficiency; medical images; nearest neighbor search; privacy
Categories
Funding
- National Natural Science Foundation of China [61501080, 61572095, 61871064]
- Cloud Technology Endowed Professorship
- NSF CREST [HRD-1736209]
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Medical imaging plays a crucial role in medical diagnosis, and ensuring the security and privacy of medical images is essential. This paper proposes a secure and efficient scheme for finding the exact nearest neighbor over encrypted medical images, demonstrating its utility in Healthcare Industry 4.0.
Medical imaging is crucial for medical diagnosis, and the sensitive nature of medical images necessitates rigorous security and privacy solutions to be in place. In a cloud-based medical system for Healthcare Industry 4.0, medical images should be encrypted prior to being outsourced. However, processing queries over encrypted data without first executing the decryption operation is challenging and impractical at present. In this paper, we propose a secure and efficient scheme to find the exact nearest neighbor over encrypted medical images. Instead of calculating the Euclidean distance, we reject candidates by computing the lower bound of the Euclidean distance that is related to the mean and standard deviation of data. Unlike most existing schemes, our scheme can obtain the exact nearest neighbor rather than an approximate result. We, then, evaluate our proposed approach to demonstrate its utility.
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