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
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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},
note = {\url{https://eprint.iacr.org/2021/1058}},
url = {https://eprint.iacr.org/2021/1058}
}
