Paper 2026/985 Original: eprint.iacr.org/2026/985 ↗

A New Insight into Constructing Cryptographic Boolean Functions via Walsh Spectral Analysis

Shaozheng He
Jiongjiong Ren
Shaozhen Chen
Jiaxin Yan
Jianhua Hou
Abstract

Given that the Walsh spectrum directly determines key cryptographic properties of Boolean functions, the construction of such functions with desired spectral features has been a major research focus for decades. In this study, we first establish a unified framework for a class of specific Boolean function construction problems corresponding to Walsh transform, which we formally define as \textbf{Problem}. To tackle the \textbf{Problem}, we first designed the Iterative Walsh Recovery (IWR) algorithm as a framework, then added Forgetting and Greedy strategies for heuristic optimization to obtain the FG-IWR algorithm, and finally proved a necessary condition for optimization, ultimately proposing the Optimized Iterative Walsh Recovery (OIWR) algorithm. Through rigorous theoretical analysis and experimental validation, our algorithm simultaneously achieves theoretical guarantees, design flexibility, and computational efficiency. For application, we further present a novel construction method for low-weight correlation immune functions using the OIWR algorithm. Experimental results show that our method successfully addresses two fundamental constraints of Mesnager-Su's approach: limited construction capacity and power-of-two weight restrictions.

Metadata
Available format(s)
PDF
Category
Foundations
Publication info
Preprint.
History
2026-08-02: last updated
2026-05-18: published
Short URL
https://ia.cr/2026/985
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2026/985,
      author = {Shaozheng He and Jiongjiong Ren and Shaozhen Chen and Jiaxin Yan and Jianhua Hou},
      title = {A New Insight into Constructing Cryptographic Boolean Functions via Walsh Spectral Analysis},
      howpublished = {Cryptology {ePrint} Archive, Paper 2026/985},
      year = {2026},
      url = {https://eprint.iacr.org/2026/985}
}
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