GitHub - ShreyaCtrl/Cyber-security-IDS: This repository focuses on implementing various machine learning techniques for Intrusion Detection Systems (IDS) in cybersecurity. It includes Jupyter Notebooks demonstrating methods like Isolation Forest, K-Means clustering, and Principal Component Analysis (PCA). Written in Python, it provides practical insights into anomaly detection.

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Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
app		app
data		data
graphs		graphs
.gitignore		.gitignore
FYP 1.pdf		FYP 1.pdf
FYP_Isolation_Forest.ipynb		FYP_Isolation_Forest.ipynb
FYP_K_Means.ipynb		FYP_K_Means.ipynb
FYP_Principal_component_analysis.ipynb		FYP_Principal_component_analysis.ipynb
FYP_Robust_Co_Variance.ipynb		FYP_Robust_Co_Variance.ipynb
FYP_SGD_One_Class_SVM.ipynb		FYP_SGD_One_Class_SVM.ipynb
FYP_gaussian_mixture_model.ipynb		FYP_gaussian_mixture_model.ipynb
Final Topic submission template 1.docx		Final Topic submission template 1.docx
Final Topic submission template 1.pdf		Final Topic submission template 1.pdf
One_Class_SVM (1).ipynb		One_Class_SVM (1).ipynb

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This repository focuses on implementing various machine learning techniques for Intrusion Detection Systems (IDS) in cybersecurity. It includes Jupyter Notebooks demonstrating methods like Isolation Forest, K-Means clustering, and Principal Component Analysis (PCA). Written in Python, it provides practical insights into anomaly detection.

python cybersecurity sgd pca-analysis gans kmeans-clustering intrusion-detection-system robust-covariance

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