Paper 2024/1197 Original: eprint.iacr.org/2024/1197 ↗

Optimizing Rectangle and Boomerang Attacks: A Unified and Generic Framework for Key Recovery

Qianqian Yang
Ling Song
Nana Zhang
Danping Shi
Libo Wang
Jiahao Zhao
Lei Hu
Jian Weng
Abstract

The rectangle attack has shown to be a very powerful form of cryptanalysis against block ciphers. Given a rectangle distinguisher, one expects to mount key recovery attacks as efficiently as possible. In the literature, there have been four algorithms for rectangle key recovery attacks. However, their performance varies from case to case. Besides, numerous are the applications where the attacks lack optimality. In this paper, we delve into the rectangle key recovery and propose a unified and generic key recovery algorithm, which supports any possible attacking parameters. Not only does it encompass the four existing rectangle key recovery algorithms, but it also reveals five new types of attacks that were previously overlooked. Further, we put forward a counterpart for boomerang key recovery attacks, which supports any possible attacking parameters as well. Along with these new key recovery algorithms, we propose a framework to automatically determine the best parameters for the attack. To demonstrate the efficiency of the new key recovery algorithms, we apply them to \serpent, \aes-192, \craft, \skinny, and \deoxysbc-256 based on existing distinguishers, yielding a series of improved attacks.

Metadata
Available format(s)
PDF
Category
Secret-key cryptography
Publication info
Preprint.
History
2024-07-25: last updated
2024-07-25: published
Short URL
https://ia.cr/2024/1197
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2024/1197,
      author = {Qianqian Yang and Ling Song and Nana Zhang and Danping Shi and Libo Wang and Jiahao Zhao and Lei Hu and Jian Weng},
      title = {Optimizing Rectangle and Boomerang Attacks: A Unified and Generic Framework for Key Recovery},
      howpublished = {Cryptology {ePrint} Archive, Paper 2024/1197},
      year = {2024},
      url = {https://eprint.iacr.org/2024/1197}
}
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