DocumentCode :
1420567
Title :
Secret Key Generation for Correlated Gaussian Sources
Author :
Nitinawarat, Sirin ; Narayan, Prakash
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Illinois, Urbana, IL, USA
Volume :
58
Issue :
6
fYear :
2012
fDate :
6/1/2012 12:00:00 AM
Firstpage :
3373
Lastpage :
3391
Abstract :
Secret key generation by multiple terminals is considered based on their observations of jointly distributed Gaussian signals, followed by public communication among themselves. Exploiting an inherent connection between secrecy generation and lossy data compression, two main contributions are made. The first is a characterization of strong secret key capacity, and entails a converse proof technique that is valid for real-valued (and not necessarily Gaussian) as well as finite-valued signals. The capacity formula acquires a simple form when the terminals observe “symmetrically correlated” jointly Gaussian signals. For the latter setup with two terminals, considering schemes that involve quantization at one terminal, the best rate of an achievable secret key is characterized as a function of quantization rate; secret key capacity is attained as the quantization rate tends to infinity. Structured codes are shown to attain the optimum tradeoff between secret key rate and quantization rate, constituting our second main contribution.
Keywords :
Gaussian processes; cryptography; data compression; Gaussian signals; converse proof technique; correlated Gaussian sources; finite-valued signals; lossy data compression; public communication; quantization rate function; secret key generation; symmetrically correlated; Bismuth; Computers; Data compression; Educational institutions; Entropy; Mutual information; Quantization; Linear code; multiterminal Gaussian source model; nested lattice code; public communication; quantization; secret key capacity; strong secrecy;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2012.2184075
Filename :
6129510
Link To Document :
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