Privacy-Protecting Mechanisms for Data Escrow and Transaction Monitoring

数据托管和交易监控的隐私保护机制

• 批准号: 0430622
• 负责人: Stanislaw Jarecki
• 金额: --
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-15 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0430622&HistoricalAwards=false
• 关键词: Privacy; Protecting; Mechanisms; Data; Escrow

Collection and monitoring of personal and business data will help government agencies detect crime, fraud, terrorism, natural disasters, and other emergencies. On the other hand, government collection and monitoring of massive mounts of data would create tremendous threats to people's privacy and an unnecessary potential for abuse. While low-tech collection of information by government agencies has been an accepted practice, the increased connectivity and transaction speed enabled by the Internet make centralized oversight of various transactional activities both more desirable and potentially more dangerous. For example, banks and individuals were for a long time required to report transactions involving more than $10,000 in cash. After 9/11, the Patriot Act asked each bank to report more patterns of suspicious activities, including for example series of smaller cash transactions or international transfers adding up to $10,000. However, since Internet banking makes it easier to conduct transactions via multiple financial institutions, what the crime fighters would really like is an ability to collect data from all financial institutions, and moreover, an ability to mine this data at will. Of course, this would be a nightmare to citizens' privacy. Indeed, the availability of all this data at the hands of a government agency is in fact bound to create new threats to the security of the banking system, possibly more serious than the threats the centralized monitoring attempted to solve. And yet, from the standpoint of cryptography, the conflict between the needs for data monitoring and the need for data privacy is not irreconcilable!Our research objective is to create mechanisms that limit the privacy threats posed by the data collection and monitoring applications, while still enabling their efficient operation. We believe that new cryptographic techniques can help resolve the conflicts between the benefits and threats posed by various data collection and monitoring scenarios. Fundamentally, we have no hope of resolving this conflict if the task of monitoring some activity for suspicious patters requires an unconstrained access to all the generated data. However, if the monitoring agency can be restricted in its access to the data, for example it can access only the data that satisfies some pre-defined suspicious patterns, then we can hope to enforce, using cryptographic mechanisms, (1) the correctness of the accessed data, and (2) the secrecy and anonymity of the data that does not meet the searched-for patterns. In other words, if conditions under which the agency should learn the data can be spelled out, then we can design data escrow protocols that allow the agency to do its monitoring work with no more intrusion on citizens' privacy then is absolutely necessary.In the financial monitoring example, the research question is to find an efficient encryption-like escrow scheme with the property that all escrowed transactions remain anonymous and undecipherable by default, except of, for example, transactions which form a pattern of international money transfers originating from the same person and adding up to $10,000.Our approach addresses a general problem of minimizing the threats posed by centralized collection and monitoring of sensitive private data. This is a novel but natural scenario for cryptography. It is also open-ended: Since different monitoring applications have different types of searched-for data patterns, this task will require a variety of approaches which are likely to produce privacy and/or correctness-enforcing mechanisms useful in other cryptographic applications. Our preliminary investigations identified the link between quite simple privacy-protected data escrow applications and deterministic encryptions, unlinkable signatures on ciphertexts, and fair two-party computation of probabilistic functionalities.This project establishes a new area of research on cryptographic tools and applications. While it's clear that centralized monitoring of various distributed activities might bring societal benefits, our research will help determine under what conditions and in what settings such monitoring can be done in a secure and maximally private manner. This research has a strong potential to impact the technical and political feasibility of data escrow and monitoring, strong PKI infrastructures (e.g. electronic IDs), and fault-tolerant cryptographic services.

收集和监控个人和商业数据将有助于政府机构发现犯罪、欺诈、恐怖主义、自然灾害和其他紧急情况。 另一方面，政府收集和监控大量数据将对人们的隐私造成巨大威胁，并可能造成不必要的滥用。 虽然政府机构以低技术手段收集信息已成为一种公认的做法，但互联网所带来的连通性和交易速度的提高，使得对各种交易活动进行集中监督既更可取，也可能更危险。 例如，长期以来，银行和个人必须报告涉及10 000美元以上现金的交易。 9/11事件后，《爱国者法案》要求每家银行报告更多的可疑活动模式，包括例如一系列小额现金交易或总额达1万美元的国际转账。 然而，由于互联网银行使通过多个金融机构进行交易变得更加容易，因此打击犯罪者真正想要的是能够从所有金融机构收集数据，并且能够随意挖掘这些数据。 当然，这对公民的隐私来说是一场噩梦。 事实上，所有这些数据在政府机构手中的可用性实际上必然会对银行系统的安全造成新的威胁，可能比集中监控试图解决的威胁更严重。 然而，从密码学的角度来看，数据监控的需求和数据隐私的需求之间的冲突并不是不可调和的！我们的研究目标是创建一种机制，限制数据收集和监控应用程序所带来的隐私威胁，同时仍然使其能够有效运行。我们相信，新的加密技术可以帮助解决各种数据收集和监控方案所带来的好处和威胁之间的冲突。 从根本上说，如果监视可疑模式的某些活动的任务需要不受约束地访问所有生成的数据，那么我们就没有希望解决这个冲突。 然而，如果监控机构可以限制其对数据的访问，例如它只能访问满足某些预定义的可疑模式的数据，那么我们可以希望使用加密机制来强制执行（1）访问数据的正确性，以及（2）不符合搜索模式的数据的保密性和匿名性。 换句话说，如果机构应该学习数据的条件可以阐明，那么我们可以设计数据托管协议，允许机构在不侵犯公民隐私的情况下进行监控工作，这是绝对必要的。在金融监控的例子中，研究的问题是找到一种有效的加密方法-类似于具有所有托管交易在默认情况下保持匿名和不可破译的属性的托管方案，除了，例如，形成源自同一人的国际汇款模式并总计达10美元的交易，000.我们的方法解决了一个一般性问题，即最大限度地减少集中收集和监视敏感私人数据所带来的威胁。 对于密码学来说，这是一个新颖但自然的场景。 它也是开放式的：由于不同的监控应用程序具有不同类型的搜索数据模式，因此该任务将需要各种可能产生在其他密码应用程序中有用的隐私和/或正确性强制机制的方法。 我们的初步研究发现了相当简单的隐私保护数据托管应用程序与确定性加密、密文上的不可验证签名和概率函数的公平两方计算之间的联系，该项目建立了密码工具和应用的新研究领域。 虽然很明显，对各种分布式活动的集中监控可能会带来社会效益，但我们的研究将有助于确定在什么条件下以及在什么环境下可以以安全和最大限度地私密的方式进行此类监控。 这项研究有很大的潜力，影响数据托管和监控，强大的PKI基础设施（如电子身份证），容错加密服务的技术和政治可行性。