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Improved Quantum Multicollision-Finding Algorithm

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Post-Quantum Cryptography (PQCrypto 2019)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11505))

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Abstract

The current paper improves the number of queries of the previous quantum multi-collision finding algorithms presented by Hosoyamada et al. at Asiacrypt 2017. Let an l-collision be a tuple of l distinct inputs that result in the same output of a target function. In cryptology, it is important to study how many queries are required to find l-collisions for random functions of which domains are larger than ranges. The previous algorithm finds an l-collision for a random function by recursively calling the algorithm for finding \((l-1)\)-collisions, and it achieves the average quantum query complexity of \(O(N^{(3^{l-1}-1) / (2 \cdot 3^{l-1})})\), where N is the range size of target functions. The new algorithm removes the redundancy of the previous recursive algorithm so that different recursive calls can share a part of computations. The new algorithm finds an l-collision for random functions with the average quantum query complexity of \(O(N^{(2^{l-1}-1) / (2^{l}-1)})\), which improves the previous bound for all \(l\ge 3\) (the new and previous algorithms achieve the optimal bound for \(l=2\)). More generally, the new algorithm achieves the average quantum query complexity of \(O\left( c^{3/2}_N N^{\frac{2^{l-1}-1}{ 2^{l}-1}}\right) \) for a random function \(f:X\rightarrow Y\) such that \(|X| \ge l \cdot |Y| / c_N\) for any \(1\le c_N \in o(N^{\frac{1}{2^l - 1}})\). With the same query complexity, it also finds a multiclaw for random functions, which is harder to find than a multicollision.

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Notes

  1. 1.

    As in our case, the BHT algorithm also focus on only quantum query complexity. Although it runs in time \(\tilde{O}(N^{1/3})\) on an idealized quantum computer, it requires \(\tilde{O}(N^{1/3})\) qubits to store data in quantum memories. Recently Chailloux et al. [CNS17] has developed a quantum 2-collision finding algorithm that runs in time \(\tilde{O}(N^{2/5})\), which is polynomially slower than the BHT algorithm but requires only \(O(\log N)\) quantum memories.

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Correspondence to Akinori Hosoyamada .

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Hosoyamada, A., Sasaki, Y., Tani, S., Xagawa, K. (2019). Improved Quantum Multicollision-Finding Algorithm. In: Ding, J., Steinwandt, R. (eds) Post-Quantum Cryptography. PQCrypto 2019. Lecture Notes in Computer Science(), vol 11505. Springer, Cham. https://doi.org/10.1007/978-3-030-25510-7_19

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  • DOI: https://doi.org/10.1007/978-3-030-25510-7_19

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