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A Comparative Study of Data Anonymization Techniques

机译:数据匿名化技术的比较研究

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In today's digital era, it is a very common practice for organizations to collect data from individual users. The collected data is then stored in multiple databases which contain personally identifiable information (PII). This may lead to a major source of privacy risk for the database. Various privacy preservation techniques have been proposed such as perturbation, anonymization and cryptographic. In this study, five anonymization techniques are compared using the same dataset. In addition to that, this study reviews the strengths and weaknesses of the different technique. In the evaluation of efficiency, suppression is found as the most efficient while swapping is in the last place. It is also revealed that swapping is the most resource-consuming technique while suppressing being less resource consuming.
机译:在今天的数字时代,组织可以从个人用户收集数据是一个非常常见的做法。然后将收集的数据存储在包含个人可识别信息(PII)的多个数据库中。这可能导致数据库的主要隐私风险来源。已经提出了各种隐私保存技术,例如扰动,匿名化和加密。在本研究中,使用相同的数据集进行比较五种匿名化技术。除此之外,本研究除了不同技术的优势和弱点。在效率的评估中,在最后一个位置时,抑制是最有效的。还透露,交换是抑制资源消耗量较少的耗费技术。

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