Attack and Anomaly Detection in IoT Sensors Using Machine Learning Approaches
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-64650-8_32
Reference19 articles.
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2. Lu, Y., Da Xu, L.: Internet of things (IoT) cybersecurity research: a review of current research topics. IEEE Internet Things J. 6(2), 2103–2115 (2018)
3. Al-Yaseen, W.L., Othman, Z.A., Nazri, M.Z.A.: Multi-level hybrid support vector machine and extreme learning machine based on modified k-means for intrusion detection system. Expert Syst. Appl. 67, 296–303 (2017)
4. Zarpelão, B.B., Miani, R.S., Kawakani, C.T., de Alvarenga, S.C.: A survey of intrusion detection in internet of things. J. Netw. Comput. Appl. 84, 25–37 (2017). https://doi.org/10.1016/j.jnca.2017.02.009
5. Mienye, I.D., Sun, Y., Wang, Z.: Prediction performance of improved decision tree-based algorithms: a review. Procedia Manuf. 35, 698–703 (2019)
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