C-Sanitized：一个文档编辑和清理的隐私模型
C-sanitized: a privacy model for document redaction and sanitization
摘要：
在当前的信息社会背景下，每天都有大量信息交换和/或发布。当文档不受控制地提供给不受信任的第三方时，这些信息的敏感性会导致严重的隐私威胁。在这种情况下，责任组织应采取适当的数据保护措施，特别是在现行数据隐私立法的保护下。要做到这一点，人类专家通常需要编辑或清理文档内容。为了减轻这一繁重的任务，本文提出了一个隐私模型的文档编辑/消毒，它提供了几个优势，在文献中的其他模型。基于数据语义和信息论的良好基础，我们的模型提供了一个框架，开发和实现自动化和固有的语义编辑/清理工具。此外，与特别编辑方法相反，我们的建议提供了先验的隐私保证，可以根据当前的数据隐私立法直观地定义。在几个用例的上下文中进行的实证测试说明了我们的模型的适用性及其模仿人类消毒剂推理的能力。
英文摘要：
Within the current context of Information Societies, large amounts of information are daily exchanged and/or released. The sensitive nature of much of this information causes a serious privacy threat when documents are uncontrollably made available to untrusted third parties. In such cases, appropriate data protection measures should be undertaken by the responsible organization, especially under the umbrella of current legislations on data privacy. To do so, human experts are usually requested to redact or sanitize document contents. To relieve this burdensome task, this paper presents a privacy model for document redaction/sanitization, which offers several advantages over other models available in the literature. Based on the well-established foundations of data semantics and the information theory, our model provides a framework to develop and implement automated and inherently semantic redaction/sanitization tools. Moreover, contrary to ad-hoc redaction methods, our proposal provides a priori privacy guarantees which can be intuitively defined according to current legislations on data privacy. Empirical tests performed within the context of several use cases illustrate the applicability of our model and its ability to mimic the reasoning of human sanitizers.
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