Paper 2021/1058

Cryptanalysis of Caesar using Quantum Support Vector Machine

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


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.

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Publication info
Preprint. MINOR revision.
CryptanalysisQuantum support vector machineQuantum computer
Contact author(s)
khj1594012 @ gmail com
thdrudwn98 @ gmail com
starj1023 @ gmail com
hwajeong84 @ gmail com
2021-08-16: received
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      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{}},
      url = {}
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