Cryptology ePrint Archive: Report 2021/1058

Cryptanalysis of Caesar using Quantum Support Vector Machine

Hyunji Kim and Gyeongju Song and 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.

Category / Keywords: implementation / Cryptanalysis, Quantum support vector machine, Quantum computer

Date: received 14 Aug 2021

Contact author: khj1594012 at gmail com, thdrudwn98 at gmail com, starj1023 at gmail com, hwajeong84 at gmail com

Available format(s): PDF | BibTeX Citation

Version: 20210816:132814 (All versions of this report)

Short URL: ia.cr/2021/1058


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