Database Matching Under Noisy Synchronization Errors

Database Matching Under Noisy Synchronization Errors
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噪声同步错误下的数据库匹配

DOI:
--
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发表时间:
2023
影响因子:
2.5
通讯作者:
E. Erkip
E. Erkip
中科院分区:
计算机科学2区
文献类型:
--
作者:
Serhat Bakirtas;E. Erkip

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通过与公开可用的相关用户数据匹配,从匿名数据中重新识别或去匿名化用户,引起了隐私问题,导致除了匿名化之外还出现了模糊处理的补充措施。最近的研究提供了对数据库匹配形式的隐私攻击在存在混淆的情况下成功的条件的基本了解。受时间索引数据库采样产生的同步错误的启发,本文提出了一个考虑混淆和同步错误的统一框架,并研究了噪声条目重复下数据库的匹配。通过研究重复模式的不同结构,设计了副本检测和种子删除检测算法,并导出了成功匹配的充分必要条件。最后,讨论了一些基本假设的变化对结果的影响,例如对抗性删除模型、无种子数据库匹配和零率制度。总的来说,我们的结果为匿名和模糊时间索引数据的隐私保护发布以及同步通道容量的密切相关问题提供了见解。
The re- identification or de-anonymization of users from anonymized data through matching with publicly available correlated user data has raised privacy concerns, leading to the complementary measure of obfuscation in addition to anonymization. Recent research provides a fundamental understanding of the conditions under which privacy attacks, in the form of database matching, are successful in the presence of obfuscation. Motivated by synchronization errors stemming from the sampling of time-indexed databases, this paper presents a unified framework considering both obfuscation and synchronization errors and investigates the matching of databases under noisy entry repetitions. By investigating different structures for the repetition pattern, replica detection and seeded deletion detection algorithms are devised and sufficient and necessary conditions for successful matching are derived. Finally, the impacts of some variations of the underlying assumptions, such as the adversarial deletion model, seedless database matching, and zero-rate regime, on the results are discussed. Overall, our results provide insights into the privacy-preserving publication of anonymized and obfuscated time-indexed data as well as the closely related problem of the capacity of synchronization channels.
同步错误下与分布无关的数据库去匿名化
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期刊: IEEE WIFS 2023
影响因子: --
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