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Secret Key Generation by Continuous Encryption Before Quantization

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Secret key generation (SKG) is a fundamental signal processing problem for security applications including wireless network security and biometric template security. For SKG, a pair (or more) of highly correlated… Click to show full abstract

Secret key generation (SKG) is a fundamental signal processing problem for security applications including wireless network security and biometric template security. For SKG, a pair (or more) of highly correlated secret vectors (SVs) need to be respectively quantized into a pair (or more) of almost identical sequences of binary bits (i.e., keys). The literatures on SKG in the wireless community almost uniformly default on a direct quantization on SVs. On the other hand, many works on biometric template security advocate a quantization on the output of a one-way function of SVs. In this paper, we present a generalized approach for SKG called continuous encryption before quantization (CEbQ). By CEbQ, a pair of SVs of limited dimension are first transformed by a continuous encryption function into a pair of sequences of quasi-continuous pseudorandom numbers (QCPRNs) of any desired length, and then these QCPRNs are quantized into keys. We show that CEbQ can yield a much lower key error rate than direct quantization subject to standardized randomness tests. Comparisons with other methods are also provided.

Keywords: secret key; encryption quantization; continuous encryption; quantization; key generation

Journal Title: IEEE Signal Processing Letters
Year Published: 2022

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