Preserving confidentiality of security policies in data outsourcing

S. Vimercati, S. Foresti, S. Jajodia, S. Paraboschi, Gerardo Pelosi, P. Samarati
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引用次数: 53

Abstract

Recent approaches for protecting information in data outsourcing scenarios exploit the combined use of access control and cryptography. In this context, the number of keys to be distributed and managed by users can be maintained limited by using a public catalog of tokens that allow key derivation along a hierarchy. However, the public token catalog, by expressing the key derivation relationships, may leak information on the security policies (authorizations) enforced by the system, which the data owner may instead wish to maintain confidential. In this paper, we present an approach to protect the privacy of the tokens published in the public catalog. Consistently with the data outsourcing scenario, our solution exploits the use of cryptography, by adding an encryption layer to the catalog. A complicating issue in this respect is that this new encryption layer should follow a derivation path that is "reversed" with respect to the key derivation. Our approach solves this problem by combining cryptography and transitive closure information. The result is an efficient solution allowing token release and traversal of the key derivation structure only to those users authorized to access the underlying resources. We also present experimental results that illustrate the behavior of our technique in large settings.
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在数据外包中保持安全策略的机密性
在数据外包场景中保护信息的最新方法是结合使用访问控制和加密技术。在这种情况下,可以通过使用允许沿层次结构派生密钥的令牌公共目录来限制用户分发和管理的密钥数量。然而,通过表示密钥派生关系,公共令牌目录可能会泄露有关系统强制执行的安全策略(授权)的信息,而数据所有者可能希望对这些信息保密。在本文中,我们提出了一种保护在公共目录中发布的令牌的隐私的方法。与数据外包场景一致,我们的解决方案通过向目录添加加密层来利用加密技术的使用。这方面的一个复杂问题是,这个新的加密层应该遵循与密钥派生“相反”的派生路径。我们的方法通过结合密码学和传递闭包信息解决了这个问题。其结果是一个有效的解决方案,仅允许授权访问底层资源的用户释放令牌和遍历密钥派生结构。我们还提出了实验结果,说明了我们的技术在大型设置中的行为。
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A Study of Users' Privacy Preferences for Data Sharing on Symptoms-Tracking/Health App. Preserving Genomic Privacy via Selective Sharing. For human eyes only: security and usability evaluation Secure communication over diverse transports: [short paper] A machine learning solution to assess privacy policy completeness: (short paper)
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