An energy-efficient and secure data inference framework for internet of health things: a pilot study

Kang JJ, Dibaei Asl M, Lou G, Yang W, Haskell-Dowland P, Zheng X (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Sensors MDPI

Publisher: MDPI

Book Volume: 21

Pages Range: 312

Journal Issue: 1

URI: https://www.mdpi.com/1424-8220/21/1/312

Authors with CRIS profile

Mahdi Dibaei Asl Computer Science 7 (Computer Networks and Communication Systems)

Involved external institutions

Edith Cowan University AU Australia (AU) Macquarie University AU Australia (AU)

How to cite

APA:

Kang, J.J., Dibaei Asl, M., Lou, G., Yang, W., Haskell-Dowland, P., & Zheng, X. (2021). An energy-efficient and secure data inference framework for internet of health things: a pilot study. Sensors, 21(1), 312.

MLA:

Kang, James Jin, et al. "An energy-efficient and secure data inference framework for internet of health things: a pilot study." Sensors 21.1 (2021): 312.

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