E-healthcare application cyber security analysis using quantum machine learning in malicious user detection
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11082-023-05854-x.pdf
Reference15 articles.
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2. Anand, A., Rani, S., Anand, D., Aljahdali, H. M., Kerr, D.: An Efficient CNN-Based Deep Learning Model to Detect Malware Attacks (CNNDMA) in 5G-IoT Healthcare Applications. Sensors. 21, 19: 6346 (2021), https://doi.org/10.3390/s21196346
3. Das, S., Das, J., Modak, S., Mazumdar, K.: Internet of things with machine learning-based smart cardiovascular disease classifier for healthcare in secure platform. In: Internet of Things and Data Mining for Modern Engineering and Healthcare Applications, pp. 45–64. Chapman and Hall/CRC (2022)
4. Dhasarathan, C., Shanmugam, M., Kumar, M., Tripathi, D., Khapre, S., Shankar, A.: A nomadic multi-agent based privacy metrics for e-health care: a deep learning approach. Multimed. Tools Appl. 1–24 (2023)
5. Khan, A.A., Laghari, A.A., Shafiq, M., Cheikhrouhou, O., Alhakami, W., Hamam, H., Shaikh, Z.A.: Healthcare ledger management: a blockchain and machine learning-enabled novel and secure architecture for the medical industry. Hum. Cent. Comput. Inf. Sci 12, 55 (2022), https://doi.org/10.22967/HCIS.2022.12.055
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