Research Area: Internet of Things
Privacy-preserving localization for Internet of Underwater Things (IoUT) plays a fundamental role in the sensing, communication and control of ocean environments. However, the unique characteristics of underwater environment make it much more difficult to achieve such a task. In this article, we are concerned with a privacy-preserving localization issue for IoUT, subjected to asynchronous clock, stratification effect and forging attack in cyber channels. In order to eliminate the influence of asynchronous clock and hide the private position information, we develop a privacy-preserving asynchronous transmission protocol, where a received signal strength (RSS)-based detection strategy is given to detect the malicious anchor nodes. Based on this, a least squares estimator is designed to estimate the position information of target. Particularly, a ray compensation strategy is incorporated into the localization estimator, such that the localization bias from assuming the straight-line transmission can be avoided. It is worth mentioning that, the proposed localization solution in this article can not only hide the private position information, but also eliminate the influences of asynchronous clock, stratification effect and forging attack. Finally, simulation and experiment results are conducted to reveal that the proposed localization solution outperforms the other existing works in terms of localization accuracy and effectiveness.
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Author(s) Name: Jing Yan; Yuan Meng; Xiaoyuan Luo; Xinping Guan
Journal name: IEEE Internet of Things Journal
Conferrence name:
Publisher name: IEEE
DOI: 10.1109/JIOT.2021.3068298
Volume Information: Volume: 8, Issue: 18, Sept.15, 15 2021, Page(s): 14338 - 14354
