通过应用密码学将移动性与传染病私下联系起来
Privately Connecting Mobility to Infectious Diseases via Applied Cryptography
摘要：
最近的研究表明，手机移动数据具有独特的潜力，可以为人类移动以及感染性疾病的传播建立准确的模型。虽然先前的研究完全依赖于移动网络运营商的订户的汇总数据来建模疾病动态，但可能优选的是仅考虑受感染个体的汇总移动数据。显然，天真地将移动电话数据与健康记录联系起来会侵犯隐私，因为这可能会跟踪感染者的移动模式，泄露有关感染者的信息，或者两者兼而有之。这项工作旨在开发一种解决方案，报告受感染个人的聚合移动电话位置数据，同时仍然保持符合隐私期望。为了实现隐私，我们使用同态加密，验证技术来自零知识证明，和差分隐私。我们的协议的开源实现可以在70分钟内处理800万用户。
英文摘要：
Recent work has shown that cell phone mobility data has the unique potential to create accurate models for human mobility and consequently the spread of infected diseases. While prior studies have exclusively relied on a mobile network operator's subscribers' aggregated data in modelling disease dynamics, it may be preferable to contemplate aggregated mobility data of infected individuals only. Clearly, naively linking mobile phone data with health records would violate privacy by either allowing to track mobility patterns of infected individuals, leak information on who is infected, or both. This work aims to develop a solution that reports the aggregated mobile phone location data of infected individuals while still maintaining compliance with privacy expectations. To achieve privacy, we use homomorphic encryption, validation techniques derived from zero-knowledge proofs, and differential privacy. Our protocol's open-source implementation can process eight million subscribers in 70 minutes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
