LIOC - DDoS dataset

Published: 28 February 2024| Version 1 | DOI: 10.17632/gm4w4kc3p7.1
Contributors:
Danny Acosta,

Description

This dataset presents the development and implementation to evaluate the effectiveness of a DDoS attack mitigation or generation. In this contribution we manage three network environments, namely, 1) on a Cloud, 2) On-Premise, and 3) a segmented network. Leveraging insights from prior investigations of our group, on the creation of machine learning algorithms to replicate (using Generative Adversarial Networks, GANs) and detected of DDos attacks using a group of Machine Learning and Deep Learning algorithms, such as: Convolutional Neural Networks (CNN), K-nearest neighbors (KNN), and tree based XGBoost.

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Institutions

Universidad Tecnologica de Panama, Universidad Politecnica de Puerto Rico

Categories

Computer Network, Cybersecurity, Data Network, Network Security, Denial-of-Service Attack, Information Security, Intrusion Analysis, Cloud Security

Licence