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)
- 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
-
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} }