Low-density random matrices for secret key extraction
Author(s)Zhou, Hongchao; Chandar, Venkat B.; Wornell, Gregory W.
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Secret key extraction, the task of extracting a secret key from shared information that is partially known by an eavesdropper, has important applications in cryptography. Motivated by the requirements of high-speed quantum key distribution, we study secret-key extraction methods with simple and efficient hardware implementations, in particular, linear transformations based on low-density random matrices. We show that this method can achieve the information-theoretic upper bound (conditional Shannon entropy) on efficiency for a wide range of key-distribution systems. In addition, we introduce a numerical method that allows us to tightly estimate the quality of the generated secret key in the regime of finite block length, and use this method to demonstrate that low-density random matrices achieve very high performance for secret key extraction.
DepartmentLincoln Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Research Laboratory of Electronics
Proceedings of the 2013 IEEE International Symposium on Information Theory
Institute of Electrical and Electronics Engineers (IEEE)
Zhou, Hongchao, Venkat Chandar, and Gregory Wornell. “Low-Density Random Matrices for Secret Key Extraction.” 2013 IEEE International Symposium on Information Theory (July 2013).
Author's final manuscript