‘애플과 구글의 코로나 접촉 추적 사양’에 대한 보안성 평가 및 검증 가능한 연산을 이용한 개선
Security Analysis on ‘Privacy-Preserving Contact Tracing Specifications by Apple and Google' and Improvement with Verifiable Computations
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그동안 COVID-19의 확산을 막고 사회를 정상화하려는 노력이 있었고, 감염 확산 탐지를 위해선 접촉자 추적 기술이 필수적이다. 하지만, 정부에 의한 접촉 추적 과정에서 공개된 감염자의 개인 정보 침해에 대한 우려가 제기되고 있고, 이에 Google과 Apple은 개인 정보 보호와 보안을 고려하여 정부와 보건 기관의 COVID-19 확산 방지에 대한 노력을 도울 수 있도록 블루투스 기술을 사용한 접촉 추적 기술을 발표했다. 그러나 더 나은 접촉 추적 기술을 제시하기 위해서는 체계적으로 보안 위협 및 취약점 도출하는 과정이 필요하다. 본 논문에서는 STRIDE, LINDDUN 위협 모델링을 통해 COVID-19 접촉 추적 기술에 대한 보안성을 분석하고, 이것을 기반으로 Zero-knowledge Succinctness Non-interactive Arguments of Knowledges(zkSNARKs)와 Public Key Infrastructure(PKI)를 이용해 실질적인 데이터 무결성과 개인 정보 보호 보장 방식을 제안한다.
Abstract
There has been global efforts to prevent the further spread of the COVID-19 and get society back to normal. ‘Contact tracing’ is a crucial way to detect the infected person. However the contact tracing makes another concern about the privacy violation of the personal data of infected people, released by governments. Therefore Google and Apple are announcing a joint effort to enable the use of Bluetooth technology to help governments and health agencies reduce the spread of the virus, with user privacy and security central to the design. However, in order to provide the improved tracing application, it is necessary to identify potential security threats and investigate vulnerabilities for systematically. In this paper, we provide security analysis of Privacy-Preserving COVID-19 Contact Tracing App with STRIDE and LINDDUN threat models. Based on the analysis, we propose to adopt a verifiable computation scheme, Zero-knowledge Succinctness Non-interactive Arguments of Knowledges (zkSNARKs) and Public Key Infrastructure (PKI) to ensure both data integrity and privacy protection in a more practical way.
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