International Association
for Cryptologic Research

We present new techniques for garbling mixed arithmetic and boolean circuits, utilizing the homomorphic secret sharing scheme introduced by Roy \& Singh (Crypto 2021), along with the half-tree protocol developed by Guo et al. (Eurocrypt 2023). Compared to some two-party interactive protocols, our mixed garbling only requires several times $(<10)$ more communication cost. We construct the bit decomposition/composition gadgets with communication cost $O((\lambda+\lambda_{\text{DCR}}/k)b)$ for integers in the range $(-2^{b-1}, 2^{b-1})$, requiring $O(2^k)$ computations for the GGM-tree. Our approach is compatible with constant-rate multiplication protocols, and the cost decreases as $k$ increases. Even for a small $k=8$, the concrete efficiency ranges from $6\lambda b$ ($b \geq 1000$ bits) to $9\lambda b$ ($b \sim 100$ bits) per decomposition/composition. In addition, we develop the efficient gadgets for mod $q$ and unsigned truncation based on bit decomposition and composition. We construct efficient arithmetic gadgets over various domains. For bounded integers, we improve the multiplication rate in the work of Meyer et al. (TCC 2024) from $\textstyle\frac{\zeta-2}{\zeta+1}$ to $\frac{\zeta-2}{\zeta}$. We propose new garbling schemes over other domains through bounded integers with our modular and truncation gadgets, which is more efficient than previous constructions. For $\mathbb{Z}_{2^b}$, additions and multiplication can be garbled with a communication cost comparable to our bit decomposition. For general finite field $\mathbb{F}_{p^n}$, particularly for large values of $p$ and $n$, we garble the addition and multiplication at the cost of $O((\lambda+\lambda_{\text{DCR}}/k)b)$, where $b = n\lceil \log p \rceil$. For applications to real numbers, we introduce an ``error-based'' truncation that makes the cost of multiplication dependent solely on the desired precision. \keywords{Garbled circuit \and Mixed circuits \and Secure computation}

We present analysis of time-space tradeoffs for both the search and decision variants of the $k$-collision problem in algorithmic perspective, where $k \in \left[2, O(\operatorname{polylog}(N))\right]$ and the underlying function is $f_{N,M} : [N] \rightarrow [M]$ with $M \geq N$. In contrast to prior work that focuses either on 2-collisions or on random functions with $M = N$, our results apply to both random and arbitrary functions and extend to a broader range of $k$. The tradeoffs are derived from explicit algorithmic constructions developed in this work, especially for decision problems when $k\geq3$. For 2-collision problems, we show that for any random function $f_{N,M}$ with $M \geq N$, the time-space tradeoff for finding all 2-collisions follows a single curve $T=\widetilde{O}\left(\frac{N^{3/2}}{\sqrt{S}}\right)$, where $T$ denotes time complexity and $S$ denotes available space. This tradeoff also extends to arbitrary functions with at most $O(N)$ total 2-collisions. For 3-collision problems, we identify two time-space tradeoff curves for the search variant over random functions, depending on the available space $S$. For arbitrary functions, we show that the decision problem can be solved with a tradeoff of $T=\widetilde{O}\left(\frac{N^{3/2}}{\sqrt{S}} + \frac{N}{S}\frac{n_2}{n_3}\right)$, where $n_{i}$ denotes the number of $i$-collisions. Surprisingly, for random functions, the decision problem for 3-collision shares the same time-space tradeoff as the 2-collision case $T=\widetilde{O}\left(\frac{N^{3/2}}{\sqrt{S}}\right)$. For general $k$-collision problems, we extend these results to show that the decision problem over arbitrary functions can be solved in time $T=\widetilde{O}\left(\frac{N^{3/2}}{\sqrt{S}} + \frac{N}{S}\frac{n_2}{n_k}\right)$. For the search problem over random functions, we derive two time-space tradeoffs based on the space $S$, yielding approximately $S^{1/(k-2)}$ or $S^{1/(2k-2)}$-fold speedups compared to the low-memory setting $S = O(\log M)$. When $M = N$, the tradeoff simplifies to one single curve with $S^{1/(k-2)}$-fold speedup.