Fundamental results on secret sharing schemes (SSSs) are discussed in the setting where security and share size are measured by (conditional) min-entropies. We first formalize a unified framework of SSSs based on (conditional) Rέnyi entropies, which includes SSSs based on Shannon and min entropies etc. as special cases. By deriving the lower bound of share sizes in terms of Rέnyi entropies based on the technique introduced by Iwamoto-Shikata, we obtain the lower bounds of share sizes measured by min entropies as well as by Shannon entropies in a unified manner. As the main contributions of this paper, we show two existential results of non-perfect SSSs based on min-entropies under several important settings. We first show that there exists a nonperfect SSS for arbitrary binary secret information and arbitrary monotone access structure. In addition, for every integers k and n (k ≤ n), we prove that the ideal non-perfect (k, n)-threshold scheme exists even if the distribution of the secret is not uniformly distributed.
Fundamental results on secret sharing schemes (SSSs) are discussed in the setting where security and share size are measured by (conditional) min-entropies. We first formalize a unified framework of SSSs based on (conditional) Rέnyi entropies, which includes SSSs based on Shannon and min entropies etc. as special cases. By deriving the lower bound of share sizes in terms of Rέnyi entropies based on the technique introduced by Iwamoto-Shikata, we obtain the lower bounds of share sizes measured by min entropies as well as by Shannon entropies in a unified manner. As the main contributions of this paper, we show two existential results of non-perfect SSSs based on min-entropies under several important settings. We first show that there exists a nonperfect SSS for arbitrary binary secret information and arbitrary monotone access structure. In addition, for every integers k and n (k ≤ n), we prove that the ideal non-perfect (k, n)-threshold scheme exists even if the distribution of the secret is not uniformly distributed.
In a secret sharing scheme, a secret s is divided into multiple shares and distributed among n participants. As more shares are collected, the mutual information between the secret and the shares increases monotonically. In the perfect case, the best known explicit lower bound on the share size is given by k2k−1⋅H(s), where H(s) is the entropy of the secret and k is the largest integer such that n ≥ 2k+k−2. This paper considers the non-perfect case, in which each share reveals at most a L1 fraction of the secret's entropy, for an integer L > 1. A prior result in this setting provides a lower bound of kL2k−1⋅H(s), under the condition n ≥ 2k+k+L−3. We provide a new lower bound that approaches the perfect-case bound, namely k2k−2+1/L⋅H(s), which holds under the condition n ≥ 2k+k+2L−4. The proof generalizes perfect-case techniques by increasing the number of participants by 2(L−1). These results refine our understanding of the trade-off between share size and information leakage in non-perfect secret sharing. In particular, we construct non-perfect access structures that nearly attain the perfect lower bound with fewer participants than previous non-perfect bounds, thus complementing and extending prior work.
Different security notions of secret sharing schemes have been proposed by different information measures. Entropies, such as Shannon entropy and min entropy, are frequently used in the setting security notions for secret sharing schemes. Different to the entropies, Kolmogorov complexity was also defined and used in study the security of individual instances for secret sharing schemes. This paper is concerned with these security notions for secret sharing schemes defined by the variational measures, including Shannon entropy, guessing probability, min entropy and Kolmogorov complexity.
The following standard relaxations of perfect security for secret sharing schemes (SSSs) exist in the literature:quasi-perfect,almost-perfect, andstatistical. Understanding the power of these relaxations on the efficiency of SSSs, measured via a parameter calledinformation ratio, is a long-standing open problem. In this article, we introduce and study an extremely relaxed security notion, calledpartial security, for which it is only required that any qualified set gains strictly more information about the secret than any unqualified one. To get a meaningful efficiency measure, we normalize the (standard) information ratio of such schemes by an appropriate parameter and refer to the new measure aspartial information ratio. We present three main results in this paper.First, we prove that partial and perfect information ratios coincide for the class of linear SSSs.Second, we prove that for the general (i.e., non-linear) class of SSSs, partial and statistical information ratios are equal.Third, we show that partial and almost-perfect information ratios do not coincide for the class of mixed-linear schemes (i.e., schemes constructed by combining linear schemes with different underlying finite fields). We also use the notion of partial secret sharing to strengthen and unify the previousdecompositiontheorems for constructing SSSs.
The known secret-sharing schemes for most access structures are not efficient; even for a one-bit secret the length of the shares in the schemes is 2O(n), wherenis the number of participants in the access structure. It is a long standing open problem to improve these schemes or prove that they cannot be improved. The best known lower bound is by Csirmaz, who proved that there exist access structures withnparticipants such that the size of the share of at least one party isn/logntimes the secret size. Csirmaz's proof uses Shannon information inequalities, which were the only information inequalities known when Csirmaz published his result. On the negative side, Csirmaz proved that by only using Shannon information inequalities one cannot prove a lower bound of ω(n) on the share size. In the last decade, a sequence of non-Shannon information inequalities were discovered. In fact, it was proved that there are infinity many independent information inequalities even in four variables. This raises the hope that these inequalities can help in improving the lower bounds beyondn. However, we show that any information inequality with four or five variables cannot prove a lower bound of ω(n) on the share size. In addition, we show that the same negative result holds for all information inequalities with more than five variables that are known to date.
Abstract. In this paper, information theoretic cryptography is discussed based on conditional Rényi entropies. Our discussion focuses not only on cryptography but also on the definitions of conditional Rényi entropies and the related information theoretic inequalities. First, we revisit conditional Rényi entropies, and clarify what kind of properties are required and actually satisfied. Then, we propose security criteria based on Rényi entropies, which suggests us deep relations between (conditional) Rényi entropies and error probabilities by using several guessing strategies. Based on these results, unified proof of impossibility, namely, the lower bounds of key sizes is derived based on conditional Rényi entropies. Our model and lower bounds include the Shannon’s perfect secrecy, and the minentropy based encryption presented by Dodis, and Alimomeni and Safavi-Naini. Finally, new optimal symmetric key cryptography and almost optimal secret sharing schemes are proposed which achieve our lower bounds.
Secret sharing schemes are a fundamental cryptographic tool for securely distributing sensitive information among multiple parties according to a specified access structure. For a given access policy, several schemes with different levels of efficiency may exist. One of the main parameters in this analysis is the share size and a central goal is to minimize it. This thesis studies the complexity of secret sharing schemes by focusing on lower and upper bounds on the share size for arbitrary and explicit access structures. The main objective is to collect the most relevant results in the literature, ranging from early lower bounds due to Karnin et al. and Csirmaz and upper-bound of Liu and Vaikuntanathan to recent advances that have significantly improved known bounds. Despite this progress, a significant gap between lower and upper bounds remains, leaving the determination of the optimal share size an open problem.