International Association
for Cryptologic Research

Motivated by secure database search, we present secure computation protocols for a function $f$ in the client-servers setting, where a client obtains $f(x)$ on a private input $x$ by communicating with multiple servers each holding $f$. Specifically, we propose generic compilers from passively secure protocols, which only keep security against servers following the protocols, to actively secure protocols, which guarantee privacy and correctness even against malicious servers. Our compilers are applied to protocols computing any class of functions, and are efficient in that the overheads in communication and computational complexity are only polynomial in the number of servers, independent of the complexity of functions. We then apply our compilers to obtain concrete actively secure protocols for various functions including private information retrieval (PIR), bounded-degree polynomials and constant-depth circuits. For example, our actively secure PIR protocols achieve exponentially better computational complexity in the number of servers than the currently best-known protocols. Furthermore, our protocols for polynomials and constant-depth circuits reduce the required number of servers compared to the previous actively secure protocols. In particular, our protocol instantiated from the sparse learning parity with noise (LPN) assumption is the first actively secure protocol for polynomials which has the minimum number of servers, without assuming fully homomorphic encryption.

An $\ell$-server Private Information Retrieval (PIR) scheme enables a client to retrieve a data item from a database replicated among $\ell$ servers while hiding the identity of the item. It is called $b$-error-correcting if a client can correctly compute the data item even in the presence of $b$ malicious servers. It is known that $b$-error correction is possible if and only if $\ell>2b$. In this paper, we first prove that if error correction is perfect, i.e., the client always corrects errors, the minimum communication cost of $b$-error-correcting $\ell$-server PIR is asymptotically equal to that of regular $(\ell-2b)$-server PIR as a function of the database size $n$. Secondly, we formalize a relaxed notion of statistical $b$-error-correcting PIR, which allows non-zero failure probability. We show that as a function of $n$, the minimum communication cost of statistical $b$-error-correcting $\ell$-server PIR is asymptotically equal to that of regular $(\ell-b)$-server one, which is at most that of $(\ell-2b)$-server one. Our main technical contribution is a generic construction of statistical $b$-error-correcting $\ell$-server PIR for any $\ell>2b$ from regular $(\ell-b)$-server PIR. We can therefore reduce the problem of determining the optimal communication complexity of error-correcting PIR to determining that of regular PIR. In particular, our construction instantiated with the state-of-the-art PIR schemes and the previous lower bound for single-server PIR result in a separation in terms of communication cost between perfect and statistical error correction for any $\ell>2b$.

Randomness is an essential resource for cryptography. For practical randomness generation, the security notion of pseudorandom generators (PRGs) intends to automatically preserve (computational) security of cryptosystems when used in implementation. Nevertheless, some opposite case such as in computational randomness extractors (Barak et al., CRYPTO 2011) is known (but not yet systematically studied so far) where the security can be lost even by applying secure PRGs. The present paper aims at pushing ahead the observation and understanding about such a phenomenon; we reveal such situations at layers of primitives and protocols as well, not just of building blocks like randomness extractors. We present three typical types of such cases: (1) adversaries can legally see the seed of the PRGs (including the case of randomness extractors); (2) the set of "bad" randomness may be not efficiently recognizable; (3) the formulation of a desired property implicitly involves non-uniform distinguishers for PRGs. We point out that the semi-honest security of multiparty computation also belongs to Type 1, while the correctness with negligible decryption error probability for public key encryption belongs to Types 2 and 3. We construct examples for each type where a secure PRG (against uniform distinguishers only, for Type 3) does not preserve the security/correctness of the original scheme; and discuss some countermeasures to avoid such an issue.

Non-interactive secure multiparty computation (NIMPC) is a variant of secure computation which allows each of $n$ players to send only a single message depending on his input and correlated randomness. Abelian programs, which can realize any symmetric function, are defined as functions on the sum of the players' inputs over an abelian group and provide useful functionalities for real-world applications. We improve and extend the previous results in the following ways: \begin{itemize} \item We present NIMPC protocols for abelian programs that improve the best known communication complexity. If inputs take any value of an abelian group $\mathbb{G}$, our protocol achieves the communication complexity $O(|\mathbb{G}|(\log|\mathbb{G}|)^2)$ improving $O(|\mathbb{G}|^2n^2)$ of Beimel et al. (Crypto 2014). If players are limited to inputs from subsets of size at most $d$, our protocol achieves $|\mathbb{G}|(\log|\mathbb{G}|)^2(\max\{n,d\})^{(1+o(1))t}$ where $t$ is a corruption threshold. This result improves $|\mathbb{G}|^3(nd)^{(1+o(1))t}$ of Beimel et al. (Crypto 2014), and even $|\mathbb{G}|^{\log n+O(1)}n$ of Benhamouda et al. (Crypto 2017) if $t=o(\log n)$ and $|\mathbb{G}|=n^{\Theta(1)}$. \item We propose for the first time NIMPC protocols for linear classifiers that are more efficient than those obtained from the generic construction. \item We revisit a known transformation of Benhamouda et al. (Crypto 2017) from Private Simultaneous Messages (PSM) to NIMPC, which we repeatedly use in the above results. We reveal that a sub-protocol used in the transformation does not satisfy the specified security. We also fix their protocol with only constant overhead in the communication complexity. As a byproduct, we obtain an NIMPC protocol for indicator functions with asymptotically optimal communication complexity with respect to the input length. \end{itemize}

Homomorphic secret sharing (HSS) for a function $f$ allows input parties to distribute shares for their private inputs and then locally compute output shares from which the value of $f$ is recovered. HSS can be directly used to obtain a two-round multiparty computation (MPC) protocol for possibly non-threshold adversary structures whose communication complexity is independent of the size of $f$. In this paper, we propose two constructions of HSS schemes supporting parallel evaluation of a single low-degree polynomial and tolerating multipartite and general adversary structures. Our multipartite scheme tolerates a wider class of adversary structures than the previous multipartite one in the particular case of a single evaluation and has exponentially smaller share size than the general construction. While restricting the range of tolerable adversary structures (but still applicable to non-threshold ones), our schemes perform $\ell$ parallel evaluations with communication complexity approximately $\ell/\log\ell$ times smaller than simply using $\ell$ independent instances. We also formalize two classes of adversary structures taking into account real-world situations to which the previous threshold schemes are inapplicable. Our schemes then perform $O(m)$ parallel evaluations with almost the same communication cost as a single evaluation, where $m$ is the number of parties.