The More the Merrier! On Total Coding and Lattice Problems and the Complexity of Finding Multicollisions

Authors Huck Bennett, Surendra Ghentiyala, Noah Stephens-Davidowitz



PDF
Thumbnail PDF

File

LIPIcs.ITCS.2025.14.pdf
  • Filesize: 0.83 MB
  • 22 pages

Document Identifiers

Author Details

Huck Bennett
  • University of Colorado Boulder, CO, USA
Surendra Ghentiyala
  • Cornell University, Ithaca, NY, USA
Noah Stephens-Davidowitz
  • Cornell University, Ithaca, NY, USA

Acknowledgements

The authors would like to thank Atri Rudra for very helpful discussions.

Cite As Get BibTex

Huck Bennett, Surendra Ghentiyala, and Noah Stephens-Davidowitz. The More the Merrier! On Total Coding and Lattice Problems and the Complexity of Finding Multicollisions. In 16th Innovations in Theoretical Computer Science Conference (ITCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 325, pp. 14:1-14:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ITCS.2025.14

Abstract

We show a number of connections between two types of search problems: (1) the problem of finding an L-wise multicollision in the output of a function; and (2) the problem of finding two codewords in a code (or two vectors in a lattice) that are within distance d of each other. Specifically, we study these problems in the total regime, in which L and d are chosen so that such a solution is guaranteed to exist, though it might be hard to find.
In more detail, we study the total search problem in which the input is a function 𝒞 : [A] → [B] (represented as a circuit) and the goal is to find L ≤ ⌈A/B⌉ distinct elements x_1,…, x_L ∈ A such that 𝒞(x_1) = ⋯ = 𝒞(x_L). The associated complexity classes Polynomial Multi-Pigeonhole Principle ((A,B)-PMPP^L) consist of all problems that reduce to this problem.
We show close connections between (A,B)-PMPP^L and many celebrated upper bounds on the minimum distance of a code or lattice (and on the list-decoding radius). In particular, we show that the associated computational problems (i.e., the problem of finding two distinct codewords or lattice points that are close to each other) are in (A,B)-PMPP^L, with a more-or-less smooth tradeoff between the distance d and the parameters A, B, and L. These connections are particularly rich in the case of codes, in which case we show that multiple incomparable bounds on the minimum distance lie in seemingly incomparable complexity classes. 
Surprisingly, we also show that the computational problems associated with some bounds on the minimum distance of codes are actually hard for these classes (for codes represented by arbitrary circuits). In fact, we show that finding two vectors within a certain distance d is actually hard for the important (and well-studied) class PWPP = (B²,B)-PMPP² in essentially all parameter regimes for which an efficient algorithm is not known, so that our hardness results are essentially tight. In fact, for some d (depending on the block length, message length, and alphabet size), we obtain both hardness and containment. We therefore completely settle the complexity of this problem for such parameters and add coding problems to the short list of problems known to be complete for PWPP.
We also study (A,B)-PMPP^L as an interesting family of complexity classes in its own right, and we uncover a rich structure. Specifically, we use recent techniques from the cryptographic literature on multicollision-resistant hash functions to (1) show inclusions of the form (A,B)-PMPP^L ⊆ (A',B')-PMPP^L' for certain non-trivial parameters; (2) black-box separations between such classes in different parameter regimes; and (3) a non-black-box proof that (A,B)-PMPP^L ∈ FP if (A',B')-PMPP^L' ∈ FP for yet another parameter regime. We also show that (A,B)-PMPP^L lies in the recently introduced complexity class Polynomial Long Choice for some parameters.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational complexity and cryptography
Keywords
  • Multicollisions
  • Error-correcting codes
  • Lattices

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. Divesh Aggarwal, Zeyong Li, and Noah Stephens-Davidowitz. A 2^n/2-time algorithm for √n-SVP and √n-Hermite SVP, and an improved time-approximation tradeoff for (H)SVP. In Eurocrypt, 2021. URL: http://arxiv.org/abs/2007.09556.
  2. Frank Ban, Kamal Jain, Christos H. Papadimitriou, Christos-Alexandros Psomas, and Aviad Rubinstein. Reductions in PPP. Information Processing Letters, 145:48-52, 2019. URL: https://doi.org/10.1016/j.ipl.2018.12.009.
  3. L. A. Bassalygo. New upper bounds for error-correcting codes. Problems of Information Transmission, pages 32-35, 1965. Google Scholar
  4. Huck Bennett, Surendra Ghentiyala, and Noah Stephens-Davidowitz. The more the merrier! on total coding and lattice problems and the complexity of finding multicollisions. In ITCS, 2025. URL: https://eccc.weizmann.ac.il/report/2024/018.
  5. Itay Berman, Akshay Degwekar, Ron D. Rothblum, and Prashant Nalini Vasudevan. Multi-collision resistant hash functions and their applications. In Eurocrypt, 2018. Google Scholar
  6. Nir Bitansky, Yael Tauman Kalai, and Omer Paneth. Multi-collision resistance: A paradigm for keyless hash functions. In STOC, 2018. Google Scholar
  7. H. F. Blichfeldt. The minimum value of quadratic forms, and the closest packing of spheres. Mathematische Annalen, 101(1):605-608, 1929. Google Scholar
  8. Romain Bourneuf, Lukáš Folwarczný, Pavel Hubáček, Alon Rosen, and Nikolaj I. Schwartzbach. PPP-completeness and extremal combinatorics. In ITCS, 2023. Google Scholar
  9. Jan Buzek and Stefano Tessaro. Collision resistance from multi-collision resistance for all constant parameters. In CRYPTO, 2024. Google Scholar
  10. Ivan Bjerre Damgård. A design principle for hash functions. In CRYPTO, 1989. Google Scholar
  11. Thomas Debris-Alazard, Léo Ducas, and Wessel P. J. van Woerden. An algorithmic reduction theory for binary codes: LLL and more. IEEE Transactions on Information Theory, 68(5):3426-3444, 2022. URL: https://doi.org/10.1109/TIT.2022.3143620.
  12. Philippe Delsarte. An algebraic approach to the association schemes of coding theory. Thesis, Universite Catholique de Louvain, 1973. Google Scholar
  13. Itai Dinur. Tight time-space lower bounds for finding multiple collision pairs and their applications. In Eurocrypt, 2020. Google Scholar
  14. I. Dumer, D. Micciancio, and M. Sudan. Hardness of approximating the minimum distance of a linear code. IEEE Transactions on Information Theory, 49(1):22-37, 2003. URL: https://doi.org/10.1109/TIT.2002.806118.
  15. Nicolas Gama and Phong Q. Nguyen. Finding short lattice vectors within Mordell’s inequality. In STOC, 2008. Google Scholar
  16. J. H. Griesmer. A bound for error-correcting codes. IBM Journal of Research and Development, 4(5):532-542, 1960. URL: https://doi.org/10.1147/RD.45.0532.
  17. Venkatesan Guruswami and Atri Rudra. Explicit codes achieving list decoding capacity: Error-correction with optimal redundancy. IEEE Trans. Inf. Theory, 54(1):135-150, 2008. URL: https://doi.org/10.1109/TIT.2007.911222.
  18. Venkatesan Guruswami, Atri Rudra, and Madhu Sudan. Essential Coding Theory. self-published, 2023. October 3rd, 2023 book version. URL: https://cse.buffalo.edu/faculty/atri/courses/coding-theory/book/web-coding-book.pdf.
  19. R. W. Hamming. Error detecting and error correcting codes. The Bell System Technical Journal, 29(2):147-160, 1950. URL: https://doi.org/10.1002/j.1538-7305.1950.tb00463.x.
  20. Yassine Hamoudi and Frédéric Magniez. Quantum time-space tradeoff for finding multiple collision pairs. ACM Trans. Comput. Theory, 15(1-2):3:1-3:22, 2023. URL: https://doi.org/10.1145/3589986.
  21. Siddhartha Jain, Jiawei Li, Robert Robere, and Zhiyang Xun. On pigeonhole principles and Ramsey in TFNP. In FOCS, 2024. Google Scholar
  22. Emil Jeřábek. Integer factoring and modular square roots. Journal of Computer and System Sciences, 82(2):380-394, 2016. URL: https://doi.org/10.1016/J.JCSS.2015.08.001.
  23. Antoine Joux. Multicollisions in iterated hash functions. application to cascaded constructions. In CRYPTO, 2004. Google Scholar
  24. Grigorii A. Kabatjanskiĭ and Vladimir I. Levenšteĭn. Bounds for packings on the sphere and in space. Problemy Peredači Informacii, 14(1):3-25, 1978. Google Scholar
  25. Ilan Komargodski, Moni Naor, and Eylon Yogev. Collision resistant hashing for paranoids: Dealing with multiple collisions. In Eurocrypt, 2018. Google Scholar
  26. Ilan Komargodski and Eylon Yogev. Personal communication, 2023. Google Scholar
  27. Arjen K. Lenstra, Hendrik W. Lenstra, Jr., and László Lovász. Factoring polynomials with rational coefficients. Mathematische Annalen, 261(4):515-534, December 1982. Google Scholar
  28. Qipeng Liu and Mark Zhandry. On finding quantum multi-collisions. In Eurocrypt, 2019. Google Scholar
  29. R. McEliece, E. Rodemich, H. Rumsey, and L. Welch. New upper bounds on the rate of a code via the Delsarte-MacWilliams inequalities. IEEE Transactions on Information Theory, 23(2):157-166, 1977. URL: https://doi.org/10.1109/TIT.1977.1055688.
  30. Ralph C. Merkle. A certified digital signature. In CRYPTO, 1989. Google Scholar
  31. Daniele Micciancio and Michael Walter. Practical, predictable lattice basis reduction. In Eurocrypt, 2016. URL: http://eprint.iacr.org/2015/1123.
  32. Hermann Minkowski. Geometrie der Zahlen. B.G. Teubner, 1910. URL: http://books.google.com/books?id=MusGAAAAYAAJ.
  33. Mridul Nandi and Douglas R. Stinson. Multicollision attacks on some generalized sequential hash functions. IEEE Transactions on Information Theory, 53(2):759-767, 2007. URL: https://doi.org/10.1109/TIT.2006.889721.
  34. Christos H. Papadimitriou. On the complexity of the parity argument and other inefficient proofs of existence. J. Comput. Syst. Sci., 48(3):498-532, 1994. URL: https://doi.org/10.1016/S0022-0000(05)80063-7.
  35. Amol Pasarkar, Christos Papadimitriou, and Mihalis Yannakakis. Extremal combinatorics, iterated pigeonhole arguments and generalizations of PPP. In ITCS, 2023. Google Scholar
  36. M. Plotkin. Binary codes with specified minimum distance. IRE Transactions on Information Theory, 6(4):445-450, 1960. URL: https://doi.org/10.1109/TIT.1960.1057584.
  37. Ron D. Rothblum and Prashant Nalini Vasudevan. Collision-resistance from multi-collision-resistance. In CRYPTO, 2022. Google Scholar
  38. Claus-Peter Schnorr. A hierarchy of polynomial time lattice basis reduction algorithms. Theor. Comput. Sci., 53(23):201-224, 1987. URL: https://doi.org/10.1016/0304-3975(87)90064-8.
  39. R. Singleton. Maximum distance q-nary codes. IEEE Transactions on Information Theory, 10(2):116-118, 1964. URL: https://doi.org/10.1109/TIT.1964.1053661.
  40. Aikaterini Sotiraki. New Hardness Results for Total Search Problems and Non-Interactive Lattice-Based Protocols. Thesis, Massachusetts Institute of Technology, 2020. URL: https://dspace.mit.edu/handle/1721.1/129310.
  41. Katerina Sotiraki, Manolis Zampetakis, and Giorgos Zirdelis. PPP-completeness with connections to cryptography. In FOCS, 2018. Google Scholar
  42. Alexander Vardy. Algorithmic complexity in coding theory and the Minimum Distance Problem. In STOC, 1997. Google Scholar
  43. Hongbo Yu and Xiaoyun Wang. Multi-collision attack on the compression functions of MD4 and 3-pass HAVAL. In ICISC, 2007. Google Scholar
  44. Victor Zyablov. An estimate of the complexity of constructing binary linear cascade codes. Probl. Peredachi Inf., 1971. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail