图数据的安全性:散列方案和定义

M. Arshad, A. Kundu, E. Bertino, K. Madhavan, A. Ghafoor
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引用次数: 14

摘要

图结构数据模型的使用正在增加——在图数据库中,用于表示生物和医疗保健数据以及地理数据。为了保护图结构数据,并为图数据库开发加密安全方案,有必要正式定义和开发合适的抗碰撞单向散列方案,并证明它们是有效的。广泛使用的Merkle哈希技术并不适合,因为图可能是有向无环图也可能是循环图。在本文中,我们正在解决这个问题。我们的贡献是:(1)定义了图的哈希方案的实用和形式化安全模型,(2)定义了完全安全哈希方案的形式化安全模型,(3)描述了图的哈希和完全安全哈希的构造,以及(4)构造的性能结果。我们的构造使用了图遍历技术,对于散列、编校和验证散列图非常有效。我们已经实现了所提出的方案,我们在真实和合成图数据集上的性能分析支持了我们的主张。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Security of graph data: hashing schemes and definitions
Use of graph-structured data models is on the rise - in graph databases, in representing biological and healthcare data as well as geographical data. In order to secure graph-structured data, and develop cryptographically secure schemes for graph databases, it is essential to formally define and develop suitable collision resistant one-way hashing schemes and show them they are efficient. The widely used Merkle hash technique is not suitable as it is, because graphs may be directed acyclic ones or cyclic ones. In this paper, we are addressing this problem. Our contributions are: (1) define the practical and formal security model of hashing schemes for graphs, (2) define the formal security model of perfectly secure hashing schemes, (3) describe constructions of hashing and perfectly secure hashing of graphs, and (4) performance results for the constructions. Our constructions use graph traversal techniques, and are highly efficient for hashing, redaction, and verification of hashes graphs. We have implemented the proposed schemes, and our performance analysis on both real and synthetic graph data sets support our claims.
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