Explainable Artificial Intelligence Enabled Intrusion Detection in the Internet of Things
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-67447-1_30
Reference17 articles.
1. Abdullahi, M., et al.: Detecting cybersecurity attacks in internet of things using artificial intelligence methods: a systematic literature review. Electronics 11(2), 198 (2022)
2. El Houda, Z.A., Brik, B., Senouci, S.M.: A novel IoT-based explainable deep learning framework for intrusion detection systems. IEEE Internet Things Maga. 5(2), 20–23 (2022)
3. Chou, D., Jiang, M.: A survey on data-driven network intrusion detection. ACM Comput. Surv. (CSUR) 54(9), 1–36 (2021)
4. Elnakib, O., Shaaban, E., Mahmoud, M., Emara, K.: Eidm: deep learning model for IoT intrusion detection systems. J. Supercomput. 1–21 (2023)
5. Kumar, V., et al.: Seamless wireless communication platform for internet of things applications. IEEE Wirel. Commun. 30, 102–110 (2022)
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