云环境下传染病接触者主动保护隐私追踪方案

Dixing Zhou, Jing Zhou, Ou Ruan
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引用次数: 0

摘要

针对目前接触者追踪方案中存在的隐私泄露和卫生部门被动追踪等问题,本文提出了一种云环境下传染病主动隐私保护接触者追踪方案。在此方案中,电信中心及时收集参与者的信息,以便卫生部门在需要时主动跟踪传染病接触者,参与者无需额外安装任何应用程序;采用伪随机数生成器对参与者的位置信息进行盲化,保护参与者的隐私;引入ElGamal加密算法及其变体,对参与者的身份进行加密,使卫生当局能够在不泄露其他参与者的任何信息的情况下正确获取联系人信息。理论分析和实验仿真表明,该方案安全有效,在大规模数据场景下也具有良好的计算性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Active Privacy-Preserving Contact Tracing Scheme for Infectious Diseases in Cloud Environment
To overcome the issues such as privacy leakage and Health Authorities passive tracking in the current contact tracing scheme, this paper proposes an active privacy-preserving contact tracing scheme for infectious diseases in cloud environments. In this scheme, Telecom Center timely collects participants' information, so that Health Authorities can proactively track the contacts of infectious diseases when needed, and participants needn't to install any additional Apps; Pseudorandom number generator is used to blind the participants' location information to protect their privacy; ElGamal encryption algorithm and its variants are introduced to encrypt the participants' identities, so that the Health Authorities can correctly obtain the information of contacts without revealing anything of other participants. Theoretical analysis and experimental simulation show that the scheme is secure and effective, and it also has good computation performance in large-scale data scenarios.
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