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On the Possibility of Basing Cryptography on \(\mathsf{EXP}\ne \mathsf{BPP}\)

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Advances in Cryptology – CRYPTO 2021 (CRYPTO 2021)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12825))

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Abstract

Liu and Pass (FOCS’20) recently demonstrated an equivalence between the existence of one-way functions (OWFs) and mild average-case hardness of the time-bounded Kolmogorov complexity problem. In this work, we establish a similar equivalence but to a different form of time-bounded Kolmogorov Complexity—namely, Levin’s notion of Kolmogorov Complexity—whose hardness is closely related to the problem of whether \(\mathsf{EXP}\ne \mathsf{BPP}\). In more detail, let Kt(x) denote the Levin-Kolmogorov Complexity of the string x; that is, \(Kt(x) = \min _{{\varPi }\in \{0,1\}^*, t \in \mathbb {N}}\{|{\varPi }| + \lceil \log t \rceil : U({\varPi }, 1^t) = x\}\), where U is a universal Turing machine, and \(U({\varPi },1^t)\) denotes the output of the program \(\varPi \) after t steps, and let \(\mathsf{MKtP}\) denote the language of pairs (xk) having the property that \(Kt(x) \le k\). We demonstrate that:

  • \(\mathsf{MKtP}\notin \mathsf{Heur}_{\mathsf{neg}}\mathsf{BPP}\) (i.e., \(\mathsf{MKtP}\) is infinitely-often two-sided error mildly average-case hard) iff infinitely-often OWFs exist.

  • \(\mathsf{MKtP}\notin \mathsf{Avg}_{\mathsf{neg}}\mathsf{BPP}\) (i.e., \(\mathsf{MKtP}\) is infinitely-often errorless mildly average-case hard) iff \(\mathsf{EXP}\ne \mathsf{BPP}\).

Thus, the only “gap” towards getting (infinitely-often) OWFs from the assumption that \(\mathsf{EXP}\ne \mathsf{BPP}\) is the seemingly “minor” technical gap between two-sided error and errorless average-case hardness of the \(\mathsf{MKtP}\) problem.

As a corollary of this result, we additionally demonstrate that any reduction from errorless to two-sided error average-case hardness for \(\mathsf{MKtP}\) implies (unconditionally) that \(\mathsf{NP}\ne \mathsf{P}\).

We finally consider other alternative notions of Kolmogorov complexity—including space-bounded Kolmogorov complexity and conditional Kolmogorov complexity—and show how average-case hardness of problems related to them characterize log-space computable OWFs, or OWFs in \(\mathsf{NC}^{0}\).

R. Pass—Supported in part by NSF Award SATC-1704788, NSF Award RI-1703846, AFOSR Award FA9550-18-1-0267, and a JP Morgan Faculty Award. This material is based upon work supported by DARPA under Agreement No. HR00110C0086. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Government or DARPA.

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Notes

  1. 1.

    We highlight that a recent result by Pass and Venkitasubramaniam [PV20] takes a step towards a positive results, showing that to prove the existence of OWFs from average-case hardness of \(\mathsf{NP}\), it suffices to prove that average-case hardness of \(\mathsf{TFNP}\) (rather than \(\mathsf{NP}\)) implies the existence of OWFs.

  2. 2.

    By “mild” average-case hardness, we here mean that no PPT algorithm is able to solve the problem with probability \(1-\frac{1}{p(n)}\) on inputs of length n, for all polynomials \(p(\cdot )\)

  3. 3.

    This non-black box aspect of our results stems from its use of [IW98].

  4. 4.

    We remark that this observation was added after becoming aware of [RS21].

  5. 5.

    We abuse the notation and say that a function f is in a class \(\mathcal {C}\) if each bit on the output of f is computable in \(\mathcal {C}\).

  6. 6.

    We remark that the constant 0.9 can be made arbitrarily small—any constants bounded away from \(\frac{2}{3}\) works as we can amplify it using a standard Chernoff-type argument.

  7. 7.

    We note that the choice of \(({\varPi }_x, t_x)\) for some x is not unique. Our argument holds if any such \(({\varPi }_x, t_x)\) is chosen.

  8. 8.

    There are also some other minor differences due to the fact that the proof in [LP20] considered the hardness of computing (or approximating) \(K^t\), whereas we here consider a decisional problem with a random threshold k, but the proof in [LP20] extends in a relatively straightforward way to deal also with decisional problems with a random threshold k.

  9. 9.

    This observation was added after becoming aware of [RS21].

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Acknowledgments

We are very grateful to Salil Vadhan for helpful discussions about the PRG construction of [IW98]. The first author also wishes to thank Hanlin Ren for helpful discussions about Levin’s notion of Kolmogorov Complexity.

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Liu, Y., Pass, R. (2021). On the Possibility of Basing Cryptography on \(\mathsf{EXP}\ne \mathsf{BPP}\). In: Malkin, T., Peikert, C. (eds) Advances in Cryptology – CRYPTO 2021. CRYPTO 2021. Lecture Notes in Computer Science(), vol 12825. Springer, Cham. https://doi.org/10.1007/978-3-030-84242-0_2

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