Exploratory evaluation of homomorphic cryptography for confidentiality protection

描述（由申请人提供）：保护患者和研究参与者的机密性是整个医疗保健连续体的关键任务，但对健康数据的共享和分析构成了障碍。机密保护会阻碍从个体到群体水平的研究，但这一重要问题的解决方案往往不令人满意，甚至在许多应用环境中没有。密码学的最新进展首次支持在加密空间中分析机密数据（例如，使其同态）-这意味着可以对加密数据进行分析，而泄露机密信息的风险很小。这对加速研究具有巨大的潜力，因为机密数据不必解密就可以分析和传播结果，但这种潜力尚未在人类受试者研究的背景下进行评估。该项目将对同态密码学进行探索性评估，用于机密健康数据的地理空间分析，并将实现四个目标： 目标1：建立一个原型安全多方计算（SCM）平台，用于计算地理空间分析所需的数学运算。该平台将对加密数据实施地理空间分析协议，从而无法重建或推断个人身份。我们将使用旨在重建个人身份的外部专家测试来评估该方法的安全性。该探索性项目将评估以下地理空间操作对加密数据的计算性能：（1）居住地点的空间权重计算;（2）聚类/热点分析;（3）按种族计算晚期诊断率;以及（4）计算诊断阶段的相对和绝对差异。这些被选为代表的地理健康分析中经常进行的地理空间计算。 目的2：应用原型系统评估前列腺癌和乳腺癌诊断阶段的种族差异。这将使用先前分析的数据评估实际可行性，并将确定未加密数据的结果是否可重现。 目标3：由北美中央癌症登记协会召集的独立工作组正式评估该方法并制定建议，该工作组包括健康研究人员，IRB主席和委员会成员，保密保护专家，疾病登记主任和密码学家。 目标4：通过同行评审的出版物和在科学会议上的发言，传播可行性分析的建议和结果。 这个高度创新和高影响力的项目可能会加速人类健康研究，导致早期的治疗进展和改善我们国家的健康。

DESCRIPTION (provided by applicant): Protecting confidentiality of patients and study participants is mission-critical across the health care continuum, yet poses obstacles for the sharing and analysis of health data. Confidentiality protection can retard research from the individual to the population level, but solutions to this important problem are often unsatisfactor and even absent in many applied settings. Recent advances in cryptography for the first time support the analysis of confidential data in the encrypted space (e.g. make it homomorphic) - meaning analyses can be conducted on encrypted data with potentially little if any risk of revealing confidential information. This has enormous potential for accelerating research since confidential data would not have to be decrypted to allow analysis and dissemination of the results, but this potential has yet to be evaluated within the context of human subjects research. This project will perform an exploratory evaluation of homomorphic cryptography for the geospatial analysis of confidential health data and will accomplish four aims: Aim 1: Build a prototype secure multi-party computation (SCM) platform for the computation of mathematical operations required in geospatial analyses. The platform will implement geospatial analysis protocols on encrypted data such that the identity of individuals cannot be reconstructed or deduced. We will evaluate security of the approach using external expert testing designed to reconstruct identity of individuals. This exploratory project will evaluate the computational performance of the following geospatial operations on encrypted data: (1) Spatial weight calculations for residential locations; (2) cluster/hotspot analysis; (3) calculation of rates of late stage diagnosis by race; and (4) calculation of relative and absolute disparities in stage at diagnosis. These have been selected to be representative of the geospatial computations frequently undertaken in geohealth analyses. Aim 2: Apply the prototype systems to assess racial disparities in stage at diagnosis for prostate and breast cancers. This will evaluate practical feasibility using previously analyzed data, and will determine whether the results with the not-encrypted data are reproducible. Aim 3: Formally evaluate the approach and formulate recommendations using an independent working group convened by the North American Association of Central Cancer Registries to include stake-holders including health researchers, IRB Chairs and committee members, experts in confidentiality protection, Directors of disease registries and cryptographers. Aim 4: Disseminate the recommendations and results of the feasibility analysis though peer-reviewed publications and presentations at scientific meeting. This highly innovative and high-impact project potentially will accelerate human health research, leading to earlier advances in treatment and improvements in our nation's health.