模拟数据泄露:通过基于场景的数据泄露,合成数据集用于描绘个人身份信息
1Indian Institute of Technology Madras, India.
Data in brief
|January 6, 2025
概括
研究人员创建了合成数据集,以研究黑客如何从数据泄露中滥用个人身份信息 (PII). 这有助于理解个人信息的分布和黑客分析的技术.
科学领域:
- 网络安全 网络安全
- 数据科学数据科学数据科学
- 信息安全 信息安全
背景情况:
- 越来越多的网络威胁和数据泄露对个人身份信息 (PII) 构成风险.
- 黑客利用泄露的数据,利用开源情报 (OSINT) 来对个人进行分析.
- 在使用真实数据违规数据集时存在道德和法律挑战.
研究的目的:
- 构建用于分析数据泄露危险的合成数据集.
- 使研究人员和专业人士能够了解个人信息的滥用和黑客分析.
- 为研究PII在违规事件中的分布提供资源.
主要方法:
- 编程生成了400万个独特个体的合成主记录.
- 创建了16个基于场景的数据集,模拟跨行业的数据泄露事件.
- 使用的PII数据类来源于"我被了吗?" 用于合成记录的创作.
主要成果:
- 开发了一个全面的合成数据集用于PII违规分析.
- 在违规事件中促进了对PII分布和相互连接的理解.
- 为生成定制合成数据提供了可重复使用的代码.
结论:
- 合成数据集提供了一种安全和道德的方法来研究数据泄露的影响.
- 生成的数据集和代码支持研究的可复制性和透明度.
- 这项工作有助于网络安全专业人员减轻与PII数据泄露相关的风险.
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