Supervised detection of IoT botnet attacks-Reference-Cited by-同舟云学术

Supervised detection of IoT botnet attacks

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Second International Conference on Data Science, E-Learning and Information Systems - DATA '19
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Author:

Alazzam Hadeel¹,Alsmady Abdulsalam²,Shorman Amaal Al¹

Affiliation:

1. The University of Jordan, Amman, Jordan

2. Jordan University of Science and Technology, Irbid, Jordan

Publisher

ACM Press

Reference15 articles.

1. Amaal Al Shorman, Hossam Faris, and Ibrahim Aljarah. 2019. Unsupervised intelligent system based on one class support vector machine and Grey Wolf optimization for IoT botnet detection. Journal of Ambient Intelligence and Humanized Computing (2019), 1--17.

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3. Herve Debar, Marc Dacier, and Andreas Wespi. 2000. A revised taxonomy for intrusion-detection systems. In Annales des télécommunications, Vol. 55. Springer, 361--378.

4. Wafa Feki-Sahnoun, Hasna Njah, Asma Hamza, Nouha Barraj, Mabrouka Mahfoudi, Ahmed Rebai, and Malika Bel Hassen. 2018. Using general linear model, Bayesian Networks and Naive Bayes classifier for prediction of Karenia selliformis occurrences and blooms. Ecological Informatics 43 (2018), 12--23.

5. Gilberto Fernandes, Joel JPC Rodrigues, Luiz Fernando Carvalho, Jalal F Al-Muhtadi, and Mario Lemes Proenga. 2018. A comprehensive survey on network anomaly detection. Telecommunication Systems (2018), 1--43.

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