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arXiv:1502.00172

Leakage-resilient Cryptography with key derived from sensitive data

Konrad Durnoga, Tomasz Kazana, Michał Zając, Maciej Zdanowicz

Published Jan 31, 2015• 0 citations
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Abstract

In this paper we address the problem of large space consumption for protocols in the Bounded Retrieval Model (BRM), which require users to store large secret keys subject to adversarial leakage. We propose a method to derive keys for such protocols on-the-fly from weakly random private data (like text documents or photos, users keep on their disks anyway for non-cryptographic purposes) in such a way that no extra storage is needed. We prove that any leakage-resilient protocol (belonging to a certain, arguably quite broad class) when run with a key obtained this way retains a similar level of security as the original protocol had. Additionally, we guarantee privacy of the data the actual keys are derived from. That is, an adversary can hardly gain any knowledge about the private data except that he could otherwise obtain via leakage. Our reduction works in the Random Oracle model.

DOI
10.48550/arxiv.1502.00172

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There has been much recent progress in constructing cryptosystems that maintain their security without requiring uniform randomness and perfect secrecy. These schemes are motivated by a diverse set of problems such as providing resilience to side-channel leakage, using weak physical sources of randomness as secret keys, and allowing deterministic encryption for high-entropy messages. The study of these problems has significantly deepened our understanding of how randomness is used in cryptographic constructions and proofs. Nevertheless, despite this progress, some basic and seemingly achievable security properties have eluded our reach. For example, we are unable to prove the security of basic tools for manipulating weak/leaky random sources, such as as pseudo-entropy generators and seed-dependent computational condensers. We also do not know how to prove leakage-resilient security of any cryptosystem with a uniquely determined secret key. In the context of deterministic encryption we do not have a standardmodel constructions achieving the strongest notion of security proposed by Bellare, Boldyreva and O’Neill (CRYPTO ’07), that would allow us to encrypt arbitrarily correlated messages of sufficiently large individual entropy. In this work, we provide broad black-box separation results, showing that the security of such primitives cannot be proven under virtually any standard cryptographic hardness assumption via a reduction that treats the adversary as a black box. We do so by formalizing the intuition that “the only way that a reduction can simulate the correctly distributed view for an attacker is to know all the secrets, in which case it does not learn anything useful from the attack”. Such claims are often misleading and clever way of getting around them allow us to achieve a wealth of positive results with imperfect/leaky randomness. However, in this work we show that this intuition can be formalized and that it indeed presents a real barrier for the examples given above. ∗IBM Research. wichs@cs.nyu.edu
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Leakage attacks, including various kinds of side-channel attacks, allow an attacker to learn partial information about the internal secrets such as the secret key and the randomness of a cryptographic system. Designing a strong, meaningful, yet achievable security notion to capture practical leakage attacks is one of the primary goals of leakage-resilient cryptography. In this work, we revisit the modelling and design of authenticated key exchange (AKE) protocols with leakage resilience. We show that the prior works on this topic are inadequate in capturing realistic leakage attacks. To close this research gap, we propose a new security notion named leakage-resilient eCK model w.r.t. auxiliary inputs (AI-LR-eCK) for AKE protocols, which addresses the limitations of the previous models. Our model allows computationally hard-to-invert leakage of both the long-term secret key and the randomness, and also addresses a limitation existing in most of the previous models where the adversary is disallowed to make leakage queries during the challenge session. As another major contribution of this work, we present a generic framework for the construction of AKE protocols that are secure under the proposed AI-LR-eCK model. An instantiation based on the decision Diffie–Hellman (DDH) assumption in the standard model is also given to demonstrate the feasibility of our proposed framework.
Cryptographic protocols, though used in a wide range of everyday tasks, are typically built for certain unrealistic ideal conditions in which the user is assumed to work. For example, one such condition that is implicitly assumed is that the user has perfect randomness that she can use as her cryptographic secret key. Another commonly made assumption is that the user runs her cryptographic tasks (such as encryption) on a device that is perfectly secure; that is, its internals are not tampered with or even observed by an adversary. In this thesis, we focus on designing cryptographic techniques that are secure under less-than-ideal conditions. In order to remove the assumption that users share perfectly random secret keys, we study the problem of privacy amplification: key agreement between two parties who both know a weak secret w, such as a password. The goal of the protocol is to convert this non-uniform secret w into a uniformly distributed string R that is fully secret from the adversary. R may then be used as a key for running symmetric cryptographic protocols (such as encryption or authentication). Because we make no computational assumptions, the entropy in R can come only from w. Thus such a protocol must minimize the entropy loss during its execution, so that R is as long as possible. In this thesis, we present the first protocol for information-theoretic key agreement that has entropy loss linear in the security parameter. The result is optimal up to constant factors. We also extend our results to the case where the users share correlated secrets w and w' . This setting occurs, for example, when the secrets are biometric readings taken at different points of time and is more generally known as information-reconciliation.