A Duality between One-Way Functions and Average-Case Symmetry of Information
Shuichi Hirahara, Rahul Ilango, Zhenjian Lu, Mikito Nanashima, Igor C. Oliveira
Abstract
Symmetry of Information (SoI) is a fundamental property of Kolmogorov complexity that relates the complexity of a pair of strings and their conditional complexities. Understanding if this property holds in the time-bounded setting is a longstanding open problem. In the nineties, Longpré and Mocas [LM93] and Longpré and Watanabe [LW95] established that if SoI holds for time-bounded Kolmogorov complexity then cryptographic one-way functions do not exist, and asked if a converse holds.
We show that one-way functions exist if and only if (probabilistic) time-bounded SoI fails on average, i.e., if there is a samplable distribution of pairs (x, y) of strings such that SoI for pK t complexity fails for many of these pairs. Our techniques rely on recent perspectives offered by probabilistic Kolmogorov complexity and meta-complexity, and reveal further equivalences between inverting one-way functions and the validity of key properties of Kolmogorov complexity in the time-bounded setting: (average-case) language compression and (average-case) conditional coding.
Motivated by these results, we investigate correspondences of this form for the worst-case hardness of NP (i.e., NP ⊈ BPP) and for the average-case hardness of NP (i.e., DistNP ⊈ HeurBPP), respectively. Our results establish the existence of similar dualities between these computational assumptions and the failure of results from Kolmogorov complexity in the timebounded setting. In particular, these characterizations offer a novel way to investigate the main hardness conjectures of complexity theory (and the relationships among them) through the lens of Kolmogorov complexity and its properties.
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