论文标题
coavoid:安全性,保存隐私的传染性疾病的联系
CoAvoid: Secure, Privacy-Preserved Tracing of Contacts for Infectious Diseases
论文作者
论文摘要
为了对抗传染病(例如SARS,COVID-19,埃博拉病毒等),政府机构,技术公司和卫生机构已经启动了各种接触追踪方法,以识别并通知暴露于感染来源的人。但是,现有的追踪方法可能导致严重的隐私和安全问题,从而阻止了它们在社区中的安全和广泛使用。为了解决这些问题,本文提出了Coavoid,这是一个分散的,保留隐私的接触跟踪系统,具有良好的可靠性和可用性。 Coavoid利用Google/Apple曝光通知(GAEN)API来实现不错的设备兼容性和运行效率。它利用GP和蓝牙低能(BLE)来可靠地验证用户信息。此外,为了增强隐私保护,Coavoid应用模糊化和混淆措施来掩盖敏感数据,使服务器和用户不可知论者对低风险和高风险人群的信息。评估表明了良好的效力和安全性。与四个最新的触点跟踪应用程序相比,Coavoid可以将数据降低至少90%,并在各种情况下同时抵抗蠕虫孔和重播攻击。
To fight against infectious diseases (e.g., SARS, COVID-19, Ebola, etc.), government agencies, technology companies and health institutes have launched various contact tracing approaches to identify and notify the people exposed to infection sources. However, existing tracing approaches can lead to severe privacy and security concerns, thereby preventing their secure and widespread use among communities. To tackle these problems, this paper proposes CoAvoid, a decentralized, privacy-preserved contact tracing system that features good dependability and usability. CoAvoid leverages the Google/Apple Exposure Notification (GAEN) API to achieve decent device compatibility and operating efficiency. It utilizes GPS along with Bluetooth Low Energy (BLE) to dependably verify user information. In addition, to enhance privacy protection, CoAvoid applies fuzzification and obfuscation measures to shelter sensitive data, making both servers and users agnostic to information of both low and high-risk populations. The evaluation demonstrates good efficacy and security of CoAvoid. Compared with four state-of-art contact tracing applications, CoAvoid can reduce upload data by at least 90% and simultaneously resist wormhole and replay attacks in various scenarios.