← 返回论文列表与筛选
阅读说明
本页整理公开书目信息，不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成，未完成全文核验，可能有误；具体假设、证明与结论请核对原文。摘要保留来源文本，未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要；缺少可靠材料时保留待补状态。
引用量采用 OpenAlex 单条关联记录，不合计多个记录；关联记录可能包含正式发表版本，不等于此版本单独引用。缺失不视为零，引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配，同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列，再参考通用方法与发表日期。
分类依据与纠错
分类依据题名和摘要中的方法词与领域语境，不使用期刊名称猜测研究方向。
反馈分类问题
正在核对关联版本…
代码、数据与补充材料
正在核对对应版本的资源…
关注这篇论文的作者
原文摘要
Statistical agencies that provide microdata for public use strive to keep the risk of disclosure of confidential information negligible. Assessing the magnitude of the risk of disclosure is not easy, however. Whether a data user or intruder attempts to obtain confidential information from a public-use file depends on the perceived costs of identifying a record, the perceived probability of success, and the information expected to be gained. In this article, a decision-theoretic framework for risk assessment that includes the intruder's objectives and strategy for compromising the data base and the information gained by the intruder is developed. Two kinds of microdata disclosure are distinguished—disclosure of a respondent's identity and disclosure of a respondent's attributes as a result of an unauthorized identification. A formula for the risk of identity disclosure is given, and a simple approximation to it is evaluated.