An average-case variant of the $k$-SUM conjecture asserts that finding $k$ numbers that sum to 0 in a list of $r$ random numbers, each of the order $r^k$, cannot be done in much less than $r^{\lceil k/2 \rceil}$ time. On the other hand, in the dense regime of parameters, where the list contains more numbers and many solutions exist, the complexity of finding one of them can be significantly improved by Wagner's $k$-tree algorithm. Such algorithms for $k$-SUM in the dense regime have many applications, notably in cryptanalysis. In this paper, assuming the average-case $k$-SUM conjecture, we prove that known algorithms are essentially optimal for $k= 3,4,5$. For $k>5$, we prove the optimality of the $k$-tree algorithm for a limited range of parameters. We also prove similar results for $k$-XOR, where the sum is replaced with exclusive or. Our results are obtained by a self-reduction that, given an instance of $k$-SUM which has a few solutions, produces from it many instances in the dense regime. We solve each of these instances using the dense $k$-SUM oracle, and hope that a solution to a dense instance also solves the original problem. We deal with potentially malicious oracles (that repeatedly output correlated useless solutions) by an obfuscation process that adds noise to the dense instances. Using discrete Fourier analysis, we show that the obfuscation eliminates correlations among the oracle's solutions, even though its inputs are highly correlated.
翻译:美元- SUM 假设的平均值为美元- 美元- 美元随机数字列表中,每份美元- 美元, 无法用远小于 美元- lcceil k/2\ rceil k/2\ rceil} 美元时间。 另一方面, 在密集的参数体系中, 清单中包含更多数字和许多解决办法, 找到其中之一的复杂程度可以通过Wagner 的 $- k$- Tree 算法得到显著改善。 在密集的制度中, 美元- 苏姆的反复计算法有许多应用, 特别是在加密分析中。 在本文中, 假设普通的美元- 美元- SUM 洞穴中, 我们证明已知的算法基本上对美元= 3, 4, 5美元。 Fork> 5, 我们证明了美元- 树算法对有限参数的优化程度。 我们还证明, 美元- XOR 的计算结果相似, 其中我们用独家或奥- 。 我们的结果是通过一个自我缩减的解算法, 例如, 以美元- 美元- 货币- 货币- 货币- 货币- 直径直立的计算法 来产生一个交易, 一种高额- 或高额- 交易 一种交易, 我们的解 一种或高额- 。