Enhancing cyber security using quantum computing and Artificial Intelligence: A review
1 Student, Executive master’s in business administration, Independent University Bangladesh, Bangladesh.
2 Student, Department of Media Studies and Journalism, University of Liberal Arts Bangladesh, Bangladesh.
3 Student, Department of Computer Science and Engineering, Daffodil International University, Bangladesh.
4 Student, Apparel Manufacturing & Technology, BGMEA University of Science & Technology, Bangladesh.
5 Student, Department of Sociology, Lalmatia Govt. women’s college, Dhaka, Bangladesh.
6 Student, Department of Electrical & Electronic Engineering, Rajshahi University of Engineering and Technology, Bangladesh.
Review Article
World Journal of Advanced Research and Reviews, 2021, 10(03), 448-456
Publication history:
Received on 17 April 2021; revised on 22 June 2021; accepted on 26 June 2021
Abstract:
The rapid development of cyber threats calls for solutions to bolster cyber security frameworks. This article reviews how Quantum Computing (QC) and AI are already beginning to address the criticisms cyber security systems typically take. Classical computing, which processes data sequentially using algorithms that are based on deterministic logic, confronts constraints from both scales and is efficient when dealing with massive datasets, resulting in slower threat detection times and a higher frequency of false positives. What's different is that quantum computing uses quantum mechanics to make data processing faster and more accurate. Using techniques like superposition and quantum-enhanced algorithms can deliver more precise threat analysis in a shorter period than can be achieved with classical methods. Quantum Machine Learning (QML) techniques such as quantum support vector machines (SVM) and variational quantum circuits handle big datasets much more efficiently than classical methods, so they enable better threat detection. Entrepreneurs also benefit from AI methods based on artificial intelligence via learning mechanisms that can automatically detect anomalies in a synergistic relationship with quantum developments to improve the accuracy of threat classification and response. With the combination of quantum algorithms and AI, cybersecurity is expected to see significantly enhanced speed, accuracy, and scalability, especially in large-scale deployment scenarios. However, problems still exist in the implementation of quantum technology - such as the need for compatible hardware and developing cryptographic methods that are in quantum times ahead. This paper points out how QC and AI could reinvent cyber security and provides an agenda that future research must take up in these areas.
Keywords:
Cyberattacks; IoT; AI; Cryptography; Quantum; IBM; Google; Cybersecurity; QSVMs; QFT; QFT; Enhancements; QAOA; SVM.
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Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0