A New Alliance of Machine Learning and Quantum Computing: Concepts, Attacks, and Challenges in IoT Networks
Rishiwal, Vinay Agarwal, Udit Yadav, Mano Tanwar, Sudeep Garg, Deepak Guizani, Mohsen
Rishiwal, Vinay
Agarwal, Udit
Yadav, Mano
Tanwar, Sudeep
Garg, Deepak
Guizani, Mohsen
Supervisor
Department
Machine Learning
Embargo End Date
Type
Journal article
Date
2025
License
Language
English
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Research Projects
Organizational Units
Journal Issue
Abstract
The Internet of Things (IoT) is a constantly expanding system connecting countless devices for seamless data collection and exchange. This has transformed decision-making with data-driven insights across different domains. However, challenges arise concerning security and computational limitations. To strengthen IoT against cyber threats and optimize resource usage, combining Quantum Computing with Machine Learning (ML) is a promising approach. ML enables computers to learn from data and detect patterns without explicit programming. By leveraging ML algorithms, vast datasets from IoT devices can be analyzed, identifying anomalies and forecasting potential security breaches. Yet, conventional ML algorithms may need help with the complexity and scale of IoT data. Quantum Computing, based on quantum mechanics, offers unparalleled computational speed and scale. Quantum ML algorithms can quickly analyze IoT datasets, identifying patterns and potential threats. This study examines the ideas behind ML, quantum computing, and their potential collaboration within IoT networks. The research focuses on the possibility of improving the security of IoT networks by integrating quantum computing approaches with ML. It also addresses the challenges and limitations of integrating ML and quantum computing in the context of IoT networks. These obstacles include hardware constraints, algorithm complexities, and the need for specialized knowledge.
Citation
V. Rishiwal, U. Agarwal, M. Yadav, S. Tanwar, D. Garg and M. Guizani, "A New Alliance of Machine Learning and Quantum Computing: Concepts, Attacks, and Challenges in IoT Networks," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2025.3535414
Source
IEEE Internet of Things Journal
Conference
Keywords
Internet of Things, Quantum computing, Security, Surveys, Machine learning, Feature extraction, Classification algorithms, Encryption, Support vector machines, Quantum algorithm
Subjects
Source
Publisher
IEEE