计算机科学
追踪
块链
接触追踪
计算机安全
互联网隐私
跟踪(心理语言学)
信息隐私
匿名
可扩展性
可追溯性
数据科学
作者
Zhike Peng,Cheng Xu,Junyou Yang,Jinbin Huang,Jianliang Xu,Xiaowen Chu
出处
期刊:International Conference on Management of Data
日期:2021-06-09
被引量:11
标识
DOI:10.1145/3448016.3459237
摘要
The eruption of a pandemic, such as COVID-19, can cause an unprecedented global crisis. Contact tracing, as a pillar of communicable disease control in public health for decades, has shown its effectiveness on pandemic control. Despite intensive research on contact tracing, existing schemes are vulnerable to attacks and can hardly simultaneously meet the requirements of data integrity and user privacy. The design of a privacy-preserving contact tracing framework to ensure the integrity of the tracing procedure has not been sufficiently studied and remains a challenge. In this paper, we propose P2B-Trace, a privacy-preserving contact tracing initiative based on blockchain. First, we design a decentralized architecture with blockchain to record an authenticated data structure of the user's contact records, which prevents the user from intentionally modifying his local records afterward. Second, we develop a zero-knowledge proximity verification scheme to further verify the user's proximity claim while protecting user privacy. We implement P2B-Trace and conduct experiments to evaluate the cost of privacy-preserving tracing integrity verification. The evaluation results demonstrate the effectiveness of our proposed system.
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