GPU Accelerated Network Anomaly Detection | Unsupervised Machine Learning | Cybersecurity Project
Автор: Shuvam Thapa
Загружено: 2026-02-07
Просмотров: 6
Описание:
In this project, I implement a GPU-accelerated unsupervised network anomaly detection system designed to identify malicious and abnormal traffic patterns efficiently.
The model is trained on the UGR’16 dataset and evaluated on the CDS IDS dataset, demonstrating strong generalization and performance improvements through GPU parallelization.
This project focuses on:
High-speed anomaly detection using GPU computing
Unsupervised learning for network security
Large-scale dataset processing and performance evaluation
gpu accelerated machine learning
network anomaly detection
unsupervised machine learning
cybersecurity project
intrusion detection system
gpu computing
network security
machine learning project
masters project cybersecurity
UGR16 dataset
CDS IDS dataset
anomaly detection machine learning
gpu vs cpu machine learning
deep learning cybersecurity
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