A Practical Fuzzy Extractor for Continuous Features

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• 关键词：Fuzzy extractor ; Code ; offset method ; Low ; Density Lattice Codes ; Key reconciliation ; Continuous source
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：10015
• 期：1
• 页码：241-258
• 全文大小：347 KB
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• 作者单位：Vladimir P. Parente (15)
  Jeroen van de Graaf (16)
  
  15. Graduate Program in Electrical Engineering, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, 31270-901, Belo Horizonte, MG, Brazil
  16. Computer Science Department, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, 31270-010, Belo Horizonte, MG, Brazil
  
• 丛书名：Information Theoretic Security
• ISBN：978-3-319-49175-2
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：10015

文摘

Many fuzzy extractors have been presented for discrete data; here we present a fuzzy extractor for continuous data. Our approach uses the code-offset method extended to \(\mathbb {R}^n\) by using lattice codes and Euclidean distance. This is accomplished in the Unconstrained Power Channel, a theoretical artifact especially developed for lattice codes used in scenarios other than telecommunication, in which the noise is assumed to be white Gaussian. To prove security we give a lower bound on the min-entropy of the common secret that an adversary necessarily faces; we also provide an upper bound. In addition we present a construction using Low-Density Lattice Codes. Our construction is more practical than existing proposals since it can be used with a feature of any dimension n and with some noise distributions that are not white Gaussian inherent to that feature.