Paper 2021/1058

Cryptanalysis of Caesar using Quantum Support Vector Machine

Hyunji Kim, Gyeongju Song, Kyoungbae Jang, and Hwajeong Seo

Abstract

Recently, artificial intelligence-based cryptanalysis techniques have been researched. In this paper, we find the key of the Caesar cipher, which is a classical cipher, by using a quantum machine learning algorithm that learns by parameterized quantum circuit instead of a classical neural network. In the case of 4-bit plaintext and key, results could not be obtained due to the limitations of the cloud environment. But in the case of 2-bit plaintext and key, an accuracy of 1.0 was achieved, and in the case of 3-bit plaintext and key, an accuracy of 0.84 was achieved. In addition, as a result of cryptanalysis for a 2-bit dataset on IBM's real quantum processor, a classification accuracy of 0.93 was achieved. In the future, we will research a qubit reduction method for cryptanalysis of longer-length plaintext and key, and a technique for maintaining accuracy in real quantum hardware.

Metadata
Available format(s)
PDF
Category
Implementation
Publication info
Preprint. MINOR revision.
Keywords
CryptanalysisQuantum support vector machineQuantum computer
Contact author(s)
khj1594012 @ gmail com
thdrudwn98 @ gmail com
starj1023 @ gmail com
hwajeong84 @ gmail com
History
2021-08-16: received
Short URL
https://ia.cr/2021/1058
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2021/1058,
      author = {Hyunji Kim and Gyeongju Song and Kyoungbae Jang and Hwajeong Seo},
      title = {Cryptanalysis of Caesar using Quantum Support Vector Machine},
      howpublished = {Cryptology {ePrint} Archive, Paper 2021/1058},
      year = {2021},
      url = {https://eprint.iacr.org/2021/1058}
}
Note: In order to protect the privacy of readers, eprint.iacr.org does not use cookies or embedded third party content.