News

GitHub11mon
Detection-of-DDoS-attack-using-machine-learning-technique
To achieve the aim of information security, a model based on machine learning ... (DDoS) attacks are demonstrated through extensive research and evaluation. Our findings emphasize the necessity of ...
GitHub8mon
Detection-of-DDOS-attacks-using-Machine-learning
This project focuses on the development and implementation of proactive defence strategies for detecting Distributed Denial of Service (DDoS) attacks. Leveraging a combination of machine learning ...
Simon Fraser University1y
Analysis of DDoS attacks on online gaming servers
The Internet is built as a best-effort service that relies primarily on trust between the end users. This architecture has widely evolved however the underlying foundational infrastructure of the ...
Frontiers2y
Protection of a smart grid with the detection of cyber- malware attacks using efficient and novel machine learning models
The primary goals of this investigation are: 1) To propose hybrid models for the protection and detection of cyber-attacks in smart grid stations. 2) To implement hybrid techniques using generic ...
IEEE5y
Detection of DDoS Attacks using Machine Learning Algorithms
Abstract: Distributed Denial of Service attack (DDoS) is the most ... In this paper, we have used machine learning based approach to detect and classify different types of network traffic flows. The ...
IEEE5y
Detection of DDoS Attacks using Machine Learning Algorithms
Abstract: Distributed Denial of Service attack (DDoS) is the most ... In this paper, we have used machine learning based approach to detect and classify different types of network traffic flows. The ...