Privacy-Aware Multidimensional Indexing
Privacy-Aware Multidimensional Indexing
复制标题
隐私感知多维索引
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
G. Saake
中科院分区：
文献类型：
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作者：
A. Grebhahn;Martin Schäler;V. Köppen;G. Saake
在法医的安全环境中删除数据库系统的数据是一个复杂的挑战。由于冗余副本和有关数据项的其他信息，仅删除数据项本身是不合适的。使用多维指数结构时会出现其他挑战。这是因为数据项的信息用于索引空间。作为最初的结果，我们提出不同的缺失水平，以克服这一挑战。基于此分类，我们分析了如何从索引中重建数据并修改索引结构以提高数据项的隐私性。其次，我们基于索引结构修改并量化了我们的修改。我们的结果表明，在某些情况下，通过修改对计算性能的影响很小的多维索引结构，可以进行法医安全删除。
Deleting data from a database system in a forensic secure environment and in a high performant way is a complex challenge. Due to redundant copies and additional information stored about data items, it is not appropriate to delete only data items themselves. Additional challenges arise when using multidimensional index structures. This is because information of data items are used to index the space. As initial result, we present different deletion levels, to overcome this challenge. Based on this classification, we analyze how data can be reconstructed from the index and modify index structures to improve privacy of data items. Second, we benchmark our index structure modifications and quantify our modifications. Our results indicate that forensic secure deletion is possible with modification of multidimensional index structures having only a small impact on computational performance, in some cases.