A review of preserving privacy in data collected from buildings with differential privacy

Kim, Jang-Hyun; H, Barry; Hong, Tianzhen; P, Marc A.

doi:10.1016/j.jobe.2022.104724

Cited by 5 publications

(1 citation statement)

References 84 publications

(147 reference statements)

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“…In the era of big data, data collection has increased dramatically, and privacy threats are unprecedented (Janghyun et al, 2022). Since the trajectory data of citizens is individual privacy, its protection should be given a very high priority (Kozak et al, 2014).…”

Section: Contact Tracingmentioning

confidence: 99%

Privacy-Preserving Contact Tracing for Curbing the Spread of Infectious Disease

Zhu

2023

Journal of Database Management

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The world is facing one of the greatest public health threats in modern history. Various techniques based on contact tracing have been developed to support non-pharmaceutical interventions. The growing evidence shows that app-based contact tracing can reduce the spread of COVID-19 if a certain proportion of the population uses the apps. However, the risk of privacy breaches that comes with such apps has long been a public concern which may hinder the uptake of the apps. In this paper, the authors attempt to find a solution to complete the spatiotemporal intersection computation without exposing the infected patient location and the user location to one another. The authors implement the solution in the WeChat applet to aid the local health center. This study conducts experiments for six scenarios to justify the applicability of the applet. Experiment results indicate that the applet is a promising non-pharmaceutical tool for curbing the spread of COVID-19.

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Section: Contact Tracingmentioning

confidence: 99%