MINI REVIEW article
Front. Quantum Sci. Technol.
Sec. Quantum Communication
Volume 4 - 2025 | doi: 10.3389/frqst.2025.1575498
This article is part of the Research TopicMachine Learning Applications in Quantum Communication NetworksView all articles
Quantum Key Distribution Through Quantum Machine Learning: A Research Review
Provisionally accepted
- adani university, Ahmedabad, Gujarat, India
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Beyond the constraints of classical encryption, the field of quantum cryptography (QC) provides a revolutionary method of secure communication. Despite traditional cryptography methods, QC protocols offer verifiable security assurances by utilizing the concepts of quantum mechanics (Goyal, 2024). Quantum teleportation (QT), quantum secret sharing (QSS), quantum secure direct communication (QSDC), and quantum key distribution (QKD) represent the four fundamental branches of quantum cryptography protocols. Unlike QKD, which is primarily concerned with the secure negotiation of cryptographic keys, QSDC introduces a novel communication paradigm that provides a comprehensive, confidential, and near-instantaneous solution by transmitting actual messages directly over a quantum channel.
Keywords: Quantum cryptography (QC), quantum machine learning (QML), quantum key distribution (QKD), Quantum convoluted neural networks (QCNN), quantum support vector machine (QSVM), Eavesdropping detection, Quantum secure direct communication (QSDC)
Received: 12 Feb 2025; Accepted: 23 Apr 2025.
Copyright: © 2025 Purohit and Vyas. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Krupa Pranav Purohit, adani university, Ahmedabad, Gujarat, India
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.