Information-Theoretic Key Agreement of Multiple Terminals—Part I

Gohari, Amin; Anantharam, Venkat

doi:10.1109/tit.2010.2050832

Cited by 118 publications

(125 citation statements)

References 17 publications

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“…2) or by investigating upper bounds other than E sq (N ). For this last question, some recent results in classical information theory 48,49 might be helpful.…”

Section: Discussionmentioning

confidence: 99%

Fundamental rate-loss tradeoff for optical quantum key distribution

2014

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Since 1984, various optical quantum key distribution (QKD) protocols have been proposed and examined. In all of them, the rate of secret key generation decays exponentially with distance. A natural and fundamental question is then whether there are yet-to-be discovered optical QKD protocols (without quantum repeaters) that could circumvent this rate-distance tradeoff. This paper provides a major step towards answering this question. Here we show that the secret key agreement capacity of a lossy and noisy optical channel assisted by unlimited two-way public classical communication is limited by an upper bound that is solely a function of the channel loss, regardless of how much optical power the protocol may use. Our result has major implications for understanding the secret key agreement capacity of optical channels-a long-standing open problem in optical quantum information theory-and strongly suggests a real need for quantum repeaters to perform QKD at high rates over long distances.

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“…2) or by investigating upper bounds other than E sq (N ). For this last question, some recent results in classical information theory 48,49 might be helpful.…”

Section: Discussionmentioning

confidence: 99%

Fundamental rate-loss tradeoff for optical quantum key distribution

2014

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“…A single-letter characterization of WSK capacity remains unresolved in general (cf. [10]). The sufficiency of the previous necessary condition is unclear even when WSK capacity is known.…”

Section: Discussionmentioning

confidence: 99%

“…From [15], [1] (and also Theorem 1), , where . Since , by Theorem 2 is securely computable if (10) We give a simple scheme for the secure computation of when , that relies on Wyner's well-known method for Slepian-Wolf data compression [20] and a derived SK generation scheme in [23], [24], and [22]. When , we can write (11) with being independent separately of and .…”

Section: Example 1: Letmentioning

confidence: 99%

When is a function securely computable?

Tyagi

Narayan

Gupta³

2011

2011 IEEE International Symposium on Information Theory Proceedings

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Abstract-A subset of a set of terminals that observe correlated signals seek to compute a function of the signals using public communication. It is required that the value of the function be concealed from an eavesdropper with access to the communication. We show that the function is securely computable if and only if its entropy is less than the capacity of a new secrecy generation model, for which a single-letter characterization is provided.

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“…Among them, information reconciliation processes are proposed in order to solve many problems in cryptography and security issues [7,8,9,11,12,13,14,15,16]. In this problem, it is assumed that Alice and Bob want to share a secret key by generating random numbers from a correlated source with noise, instead of securely transferring from Alice to Bob.…”

Section: Related Workmentioning

confidence: 99%

Generalized Upper Bound of Agreement Probability for Extracting Common Random Bits From Correlated Sources

Kim¹,

Lim²

2014

Appl. Math. Inf. Sci.

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Suppose that both Alice and Bob receive independent random bits without any bias, which are influenced by an independent noise. From the received random bits, Alice and Bob are willing to extract common randomness, without any communication. The extracted common randomness can be used for authentication or secrets. Recently, Bogdanov and Mossel derived an upper bound of the agreement probability, based on the min-entropy of outputs. In this paper, we derive a generalized upper bound of the probability of extracting common random bits from correlated sources, using the Rènyi entropy of order 1/(1 − ε), where ε is the error probability of the binary symmetric noise. It is shown that the generalized upper bound is always less than or equal to the previous bound.

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Information-Theoretic Key Agreement of Multiple Terminals—Part I

Cited by 118 publications

References 17 publications

Fundamental rate-loss tradeoff for optical quantum key distribution

Fundamental rate-loss tradeoff for optical quantum key distribution

When is a function securely computable?

Generalized Upper Bound of Agreement Probability for Extracting Common Random Bits From Correlated Sources

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