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21 IoMT-based data aggregation using quantum learning
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J. Shanthini
Abstract
In this chapter, quantum-assisted learning is introduced to aggregate data from the IoMT sensors for possible data processing and storage. The model is designed in such a way that it reduces redundant information and improves the flexibility of processing data. The entire modeling is conducted in a simulation environment to test the effectiveness of data aggregation from IoMT and its associated complexity. Experimental validation shows a reduced complex data aggregation task than with other methods.
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Abstract
In this chapter, quantum-assisted learning is introduced to aggregate data from the IoMT sensors for possible data processing and storage. The model is designed in such a way that it reduces redundant information and improves the flexibility of processing data. The entire modeling is conducted in a simulation environment to test the effectiveness of data aggregation from IoMT and its associated complexity. Experimental validation shows a reduced complex data aggregation task than with other methods.
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Kapitel in diesem Buch
- Frontmatter I
- Preface V
- Contents VII
- Biographies XI
- List of contributors XIII
- 1 Optimizing the traffic flow in VANETs using deep quantum annealing 1
- 2 Quantum annealing-based routing in UAV network 13
- 3 Cyberbullying detection of social network tweets using quantum machine learning 25
- 4 AI-driven cybersecurity modeling using quantum computing for mitigation of attacks in IOT-SDN network 37
- 5 Machine learning-based quantum modeling to classify the traffic flow in smart cities 49
- 6 IoT attack detection using quantum deep learning in large-scale networks 67
- 7 Quantum transfer learning to detect passive attacks in SDN-IOT 79
- 8 Intrusion detection framework using quantum computing for mobile cloud computing 97
- 9 Fault-tolerant mechanism using intelligent quantum computing-based error reduction codes 109
- 10 Study of quantum computing for data analytics of predictive and prescriptive analytics models 121
- 11 A review of different techniques and challenges of quantum computing in various applications 147
- 12 Review and significance of cryptography and machine learning in quantum computing 159
- 13 An improved genetic quantum cryptography model for network communication 177
- 14 Code-based post-quantum cryptographic technique: digital signature 193
- 15 Post-quantum cryptography for the detection of injection attacks in small-scale networks 207
- 16 RSA security implementation in quantum computing for a higher resilience 219
- 17 Application of quantum computing for digital forensic investigation 231
- 18 Modern healthcare system: unveiling the possibility of quantum computing in medical and biomedical zones 249
- 19 Quantum computing-assisted machine learning to improve the prediction of cardiovascular disease in healthcare system 265
- 20 Mitigating the risk of quantum computing in cyber security era 283
- 21 IoMT-based data aggregation using quantum learning 301
- Index 319
Kapitel in diesem Buch
- Frontmatter I
- Preface V
- Contents VII
- Biographies XI
- List of contributors XIII
- 1 Optimizing the traffic flow in VANETs using deep quantum annealing 1
- 2 Quantum annealing-based routing in UAV network 13
- 3 Cyberbullying detection of social network tweets using quantum machine learning 25
- 4 AI-driven cybersecurity modeling using quantum computing for mitigation of attacks in IOT-SDN network 37
- 5 Machine learning-based quantum modeling to classify the traffic flow in smart cities 49
- 6 IoT attack detection using quantum deep learning in large-scale networks 67
- 7 Quantum transfer learning to detect passive attacks in SDN-IOT 79
- 8 Intrusion detection framework using quantum computing for mobile cloud computing 97
- 9 Fault-tolerant mechanism using intelligent quantum computing-based error reduction codes 109
- 10 Study of quantum computing for data analytics of predictive and prescriptive analytics models 121
- 11 A review of different techniques and challenges of quantum computing in various applications 147
- 12 Review and significance of cryptography and machine learning in quantum computing 159
- 13 An improved genetic quantum cryptography model for network communication 177
- 14 Code-based post-quantum cryptographic technique: digital signature 193
- 15 Post-quantum cryptography for the detection of injection attacks in small-scale networks 207
- 16 RSA security implementation in quantum computing for a higher resilience 219
- 17 Application of quantum computing for digital forensic investigation 231
- 18 Modern healthcare system: unveiling the possibility of quantum computing in medical and biomedical zones 249
- 19 Quantum computing-assisted machine learning to improve the prediction of cardiovascular disease in healthcare system 265
- 20 Mitigating the risk of quantum computing in cyber security era 283
- 21 IoMT-based data aggregation using quantum learning 301
- Index 319
