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REUSABLE FUZZY EXTRACTOR BASED ON THE LEARNING-WITH-ERROR ASSUMPTION SECURE AGAINST QUANTUM ATTACKS

机译:基于对量子攻击的学习-带错误假设安全的可重复使用的模糊提取器

摘要

Described is a system for biometric based security. The system converts biometric data into a cryptographic key using a reusable fuzzy extractor process. The reusable fuzzy extractor process comprises a generation process and a reconstruction process. The generation process takes as input a public parameter and a first biometric input and outputs a public helper string and a first random string. The reconstruction process takes as input a public helper string and a second biometric input and outputs a second random string. The reusable fuzzy extractor process is reusable such that multiple public helper strings do not reveal any information about the first biometric input and the first random string. Secured data is unlocked by applying the cryptographic key for biometric security of access to secured data.
机译:描述了一种用于基于生物统计的安全性的系统。该系统使用可重复使用的模糊提取器过程将生物识别数据转换为加密密钥。可重复使用的模糊提取器过程包括生成过程和重构过程。生成过程将公共参数和第一生物特征输入作为输入,并输出公共帮助字符串和第一随机字符串。重建过程将公共帮助字符串和第二生物特征输入作为输入,并输出第二随机字符串。可重复使用的模糊提取器过程可重复使用,以使多个公共帮助字符串不会显示有关第一生物特征输入和第一随机字符串的任何信息。通过使用加密密钥来解锁安全数据,以实现对安全数据访问的生物特征安全性。

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