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.

本文针对当前信息社会的敏感性信息进行隐私保护的问题，提出了一种基于数据语义和信息理论的文档信息去标识化模型，并通过多种应用案例的实证测试，证明其具备可行性和与人工操作相近的功效。