TableGuard——保障结构化与非结构化数据的安全
TableGuard -- Securing Structured & Unstructured Data
AI总结：
TableGuard提出一种基于BERT的上下文敏感混淆方法，用于关系数据库API数据共享，平衡隐私保护与数据实用性，减少信息泄露。
摘要：
随着跨平台和组织间数据共享需求的日益增长，确保敏感信息的隐私和安全已成为一项关键挑战。本文介绍了“TableGuard”，一种针对关系数据库量身定制的创新数据混淆方法。基于先前在上下文敏感混淆方面的工作所发展的原则和技术，TableGuard应用这些方法以确保API调用仅返回混淆后的数据，从而在与第三方共享数据时保护隐私。TableGuard利用先进的上下文敏感混淆技术，用上下文合适的替代数据替换敏感数据元素。通过保持数据的关联完整性和一致性，我们的方法降低了认知失调和数据泄露的风险。我们使用基于BERT的Transformer模型展示了TableGuard的实现，该模型能够识别并混淆关系表中的敏感实体。我们的评估表明，TableGuard有效平衡了隐私保护与数据实用性，在确保混淆数据对下游应用保持功能有用的同时，最小化信息损失。结果凸显了领域特定混淆策略的重要性以及上下文长度在保持数据完整性中的作用。这项研究的意义对于需要与外部方安全共享数据的组织而言十分重大。TableGuard提供了一个健壮的框架来实现隐私保护的数据共享机制，从而为更广泛的数据隐私与安全领域做出贡献。
英文摘要：
With the increasing demand for data sharing across platforms and organizations, ensuring the privacy and security of sensitive information has become a critical challenge. This paper introduces "TableGuard". An innovative approach to data obfuscation tailored for relational databases. Building on the principles and techniques developed in prior work on context-sensitive obfuscation, TableGuard applies these methods to ensure that API calls return only obfuscated data, thereby safeguarding privacy when sharing data with third parties. TableGuard leverages advanced context-sensitive obfuscation techniques to replace sensitive data elements with contextually appropriate alternatives. By maintaining the relational integrity and coherence of the data, our approach mitigates the risks of cognitive dissonance and data leakage. We demonstrate the implementation of TableGuard using a BERT based transformer model, which identifies and obfuscates sensitive entities within relational tables. Our evaluation shows that TableGuard effectively balances privacy protection with data utility, minimizing information loss while ensuring that the obfuscated data remains functionally useful for downstream applications. The results highlight the importance of domain-specific obfuscation strategies and the role of context length in preserving data integrity. The implications of this research are significant for organizations that need to share data securely with external parties. TableGuard offers a robust framework for implementing privacy-preserving data sharing mechanisms, thereby contributing to the broader field of data privacy and security.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
