Enhancing IoT Device Security: A Comparative Analysis of Machine Learning Algorithms for Attack Detection
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-62871-9_7
Reference19 articles.
1. Adat, V., Gupta, B.B.: Security in internet of things: issues, challenges, taxonomy, and architecture. Telecommun. Syst. 67, 423–441 (2018)
2. Allam, A., Nagy, M., Thoma, G., Krauthammer, M.: Neural networks versus Logistic regression for 30 days all-cause readmission prediction. Sci. Rep. 9(1), 9277 (2019)
3. Alqarni, H., Alnahari, W., Quasim, M.T.: Internet of things (IoT) security requirements: Issues related to sensors. In: 2021 National Computing Colleges Conference (NCCC), pp. 1–6. IEEE (2021)
4. Alsharif, M., Rawat, D.B.: Study of machine learning for cloud assisted iot security as a service. Sensors 21(4), 1034 (2021)
5. Arshad, A., et al.: A novel ensemble method for enhancing internet of things device security against botnet attacks. Decis. Anal. J. 8, 100307 (2023)
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