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arXiv:1910.03757 · Leibniz international proceedings in informatics

Secret Key Agreement from Correlated Data, with No Prior Information

Marius Zimand

Published Oct 9, 2019• 0 citations
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Abstract

A fundamental question that has been studied in cryptography and in information theory is whether two parties can communicate confidentially using exclusively an open channel. We consider the model in which the two parties hold inputs that are correlated in a certain sense. This model has been studied extensively in information theory, and communication protocols have been designed which exploit the correlation to extract from the inputs a shared secret key. However, all the existing protocols are not universal in the sense that they require that the two parties also know some attributes of the correlation. In other words, they require that each party knows something about the other party's input. We present a protocol that does not require any prior additional information. It uses space-bounded Kolmogorov complexity to measure correlation and it allows the two legal parties to obtain a common key that looks random to an eavesdropper that observes the communication and is restricted to use a bounded amount of space for the attack. Thus the protocol achieves complexity-theoretical security, but it does not use any unproven result from computational complexity. On the negative side, the protocol is not efficient in the sense that the computation of the two legal parties uses more space than the space allowed to the adversary.

DOI
10.4230/lipics.stacs.2020.21

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A fundamental question that has been studied in cryptography and in information theory is whether two parties can communicate confidentially using exclusively an open channel. We consider the model in which the two parties hold inputs that are correlated in a certain sense. This model has been studied extensively in information theory, and communication protocols have been designed which exploit the correlation to extract from the inputs a shared secret key. However, all the existing protocols are not universal in the sense that they require that the two parties also know some attributes of the correlation. In other words, they require that each party knows something about the other party's input. We present a protocol that does not require any prior additional information. It uses space-bounded Kolmogorov complexity to measure correlation and it allows the two legal parties to obtain a common key that looks random to an eavesdropper that observes the communication and is restricted to use a bounded amount of space for the attack. Thus the protocol achieves complexity-theoretical security, but it does not use any unproven result from computational complexity. On the negative side, the protocol is not efficient in the sense that the computation of the two legal parties uses more space than the space allowed to the adversary.
It is known that the mutual information, in the sense of Kolmogorov complexity, of any pair of strings x and y is equal to the length of the longest shared secret key that two parties can establish via a probabilistic protocol with interaction on a public channel, assuming that the parties hold as their inputs x and y respectively. We determine the worst-case communication complexity of this problem for the setting where the parties can use private sources of random bits. We show that for some x, y the communication complexity of the secret key agreement does not decrease even if the parties have to agree on a secret key whose size is much smaller than the mutual information between x and y. On the other hand, we discuss examples of x, y such that the communication complexity of the protocol declines gradually with the size of the derived secret key. The proof of the main result uses spectral properties of appropriate graphs and the expander mixing lemma, as well as information theoretic techniques.
It is known that the mutual information, in the sense of Kolmogorov complexity, of any pair of strings x and y is equal to the length of the longest shared secret key that two parties can establish via a probabilistic protocol with interaction on a public channel, assuming that the parties hold as their inputs x and y , respectively. We determine the worst-case communication complexity of this problem for the setting where the parties can use private sources of random bits. We show that for some x , y the communication complexity of the secret key agreement does not decrease even if the parties have to agree on a secret key, the size of which is much smaller than the mutual information between x and y . However, we discuss a natural class of x , y such that the communication complexity of the protocol declines gradually with the size of the derived secret key. The proof of the main result uses the spectral properties of appropriate graphs and the expander mixing lemma, as well as information-theoretic techniques, including constraint information inequalities and Muchnik’s conditional descriptions. A preliminary version of this article was published in the proceedings of MFCS 2020. In the present version, we give full proofs of all theorems and get rid of the assumption that the number of random bits used in the communication protocols is polynomial.
It is known that noise on communication channels can be a powerful resource for certain cryptographic purposes, basically by utilizing the randomness to ensure the secrecy. In this paper, we study information theoretically secure key agreement through the use of the additive white Gaussian noise channel and public discussion. We present a protocol for key agreement that defines the computation and communications between the two communicating parties to share a common secret information, about which negligible amount of information is revealed to other third parties. We discuss the signal design, secrecy and the achievable rate of the protocol.
Abstract. We provide a simple secret-key two-party secure communication scheme, which is provably information-theoretically secure in the limited-storage-space model. The limited-storage-space model postulates an eavesdropper who can execute arbitrarily complex computations, and is only limited in the total amount of storage space (not computation space) available to him. The bound on the storage space can be arbitrarily large (e.g. terabytes), as long as it is fixed. Given this bound, the protocol guarantees that the probability of the eavesdropper of gaining any information on the message is exponentially small. The proof of our main results utilizes a novel combination of linear algebra and Kolmogorov complexity considerations. 1
We show that the mutual information, in the sense of Kolmogorov complexity, of any pair of strings x and y is equal, up to logarithmic precision, to the length of the longest shared secret key that two parties—one having x and the complexity profile of the pair and the other one having y and the complexity profile of the pair—can establish via a probabilistic protocol with interaction on a public channel. For ℓ > 2, the longest shared secret that can be established from a tuple of strings ( x 1 , …, x ℓ ) by ℓ parties—each one having one component of the tuple and the complexity profile of the tuple—is equal, up to logarithmic precision, to the complexity of the tuple minus the minimum communication necessary for distributing the tuple to all parties. We establish the communication complexity of secret key agreement protocols that produce a secret key of maximal length for protocols with public randomness. We also show that if the communication complexity drops below the established threshold, then only very short secret keys can be obtained.
We study common randomness where two parties have access to i.i.d. samples from a known random source, and wish to generate a shared random key using limited (or no) communication with the largest possible probability of agreement. This problem is at the core of secret key generation in cryptography, with connections to communication under uncertainty and locality sensitive hashing. We take the approach of treating correlated sources as a critical resource, and ask whether common randomness can be generated resource-efficiently. We consider two notable sources in this setup arising from correlated bits and correlated Gaussians. We design the first explicit schemes that use only a polynomial number of samples (in the key length) so that the players can generate shared keys that agree with constant probability using optimal communication. The best previously known schemes were both non-constructive and used an exponential number of samples. In the amortized setting, we characterize the largest achievable ratio of key length to communication in terms of the external and internal information costs, two well-studied quantities in theoretical computer science. In the relaxed setting where the two parties merely wish to improve the correlation between the generated keys of length k, we show that there are no interactive protocols using o(k) bits of communication having agreement probability even as small as 2–o(k). For the related communication problem where the players wish to compute a joint function f of their inputs using i.i.d samples from a known source, we give a simultaneous message passing protocol using 2O(c) bits where c is the interactive randomized public-coin communication complexity of f. This matches the lower bound shown previously while the best previously known upper bound was doubly exponential in c. Our schemes reveal a new connection between common randomness and unbiased error-correcting codes, e.g., dual-BCH codes and their analogues in Euclidean space.