A Survey on Botnets Attack Detection Utilizing Machine and Deep Learning Models-Reference-Cited by-同舟云学术

A Survey on Botnets Attack Detection Utilizing Machine and Deep Learning Models

Published:2023-06-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering
language:
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Author:

Alomari Dorieh¹^ORCID,Anis Fatima¹^ORCID,Alabdullatif Maryam²^ORCID,Aljamaan Hamoud¹^ORCID

Affiliation:

1. Information and Computer Science Department, King Fahd University of Petroleum and Minerals, Saudi Arabia

2. Information and Computer Science Department, King Fahd University of Petroleum and Minerals, Saudi Arabia and Imam Abdul Rahman bin Faisal University, Saudi Arabia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3593434.3593967

Reference23 articles.

1. Exploring Dataset Manipulation via Machine Learning for Botnet Traffic

2. Intelligent Techniques for Detecting Network Attacks: Review and Research Directions

3. Machine learning-based social media bot detection: a comprehensive literature review

4. Anderson Bergamini de Neira , Burak Kantarci , and Michele Nogueira . 2023. Distributed denial of service attack prediction: Challenges, open issues and opportunities. Computer Networks ( 2023 ), 109553. Anderson Bergamini de Neira, Burak Kantarci, and Michele Nogueira. 2023. Distributed denial of service attack prediction: Challenges, open issues and opportunities. Computer Networks (2023), 109553.

5. Dheeru Dua and Casey Graff. 2017. UCI Machine Learning Repository. http://archive.ics.uci.edu/ml Dheeru Dua and Casey Graff. 2017. UCI Machine Learning Repository. http://archive.ics.uci.edu/ml

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