A Review Paper on DDoS Detection Using Machine Learning
Abstract
There is almost no place in the world today that is not connected to the internet. One of the most widely used technologies is the IOT, which allows millions of devices to be connected through the internet. As this technology grows, DoS/DDoS attacks are the most common and dangerous threats. DDoS attacks are becoming more complex and they are becoming almost impossible to detect. Distributed denial of service is a subclass of denial of service. In the order to prevent DDoS attacks, many types of research have been conducted. Machine learning and deep learning are commonly used to prevent DDoS attacks. This paper describes different attack types, such as layer attacks. In this paper, we carried out a comparative analysis of machine learning algorithms to discover and classify DDoS attacks. A study of the effectiveness of detecting DoS/DDoS attacks in networks has been conducted.
References
[2] Dutta Sai Eswari1, P.V.Lakshmi, A Survey On Detection Of DDoS Attacks Using Machine Learning Approaches, Turkish Journal of Computer and Mathematics Education, 2021.
[2.1] Ancy Sherin Jose, Latha R Nair2, Varghese Paul. Towards Detecting Flooding DDOS Attacks over Software Defined Networks Using Machine Learning Techniques published in Genetic 2021
[3] Pande, S., Khamparia, A. & Gupta, D. Feature selection and comparison of classification algorithms for wireless sensor networks. J Ambient Intel Human Compute (2021).
[4] Parvinder Singh Saini, Sajal Bhatia, Sunny Behal. Detection of
DDoS attack using machine learning algorithms published in research gate in March 2020.
[5] Jiangtao Pei, Yunli Chen, Wei Ji." A DDoS Attack Detection Method Based on Machine Learning" published in ICSP 2019.
[6] Chin-Shiuh Shieh, Wan-Wei Lin, Thanh-Tuan Nguyen, Chi-Hong Chen, Mong-Fong Horng and Denis Miu. Detection of Unknown DDoS Attacks with Deep Learning and Gaussian Mixture Model, IEEE ICICT 2021.
[7] Nisha Ahuja, Gaurav Singal, Debajyoti Mukhopadhyay, Neeraj Kumar. Automated DDOS attack detection in software-defined networking published in Science Direct 2021.
[8] Alzahrani, R.J.; Alzahrani, A. Security Analysis of DDoS Attacks Using Machine Learning Algorithms in Networks Traffic.
[9] Pheeha Machaka, Olasupo Ajayi, Hloniphani Maluleke, Ferdinand Kahenga, Antoine Bagula, Kyandoghere Kyamakya, Modelling DDoS Attacks in iot Networks using Machine Learning,2021.
[10] Sara Abdalelah Abbas, Mahdi S. Almhanna, Distributed Denial of Service attacks detection System by Machine Learning Based on Dimensionality Reduction, Icmaict 2020.
[11] Swathi Sambangi and Lakshmeeswari Gondi."A Machine Learning Approach for DDoS (Distributed Denial of Service) Attack Detection Using Multiple Linear Regression" published on 25 December 2020.
[12] Alzahrani, R.J.; Alzahrani, A. Security Analysis of DDoS Attacks Using Machine Learning Algorithms in Networks Traffic. Electronics 2021, 10, 2919.https://doi.org/10.3390/electronics10232919.
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