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Awesome-Cybersecurity-Datasets

A curated list of amazingly awesome Cybersecurity datasets

langchain-kr

LangChain 공식 Document, Cookbook, 그 밖의 실용 예제를 바탕으로 작성한 한국어 튜토리얼입니다. 본 튜토리얼을 통해 LangChain을 더 쉽고 효과적으로 사용하는 방법을 배울 수 있습니다.

Intrusion-Detection-System-Using-Machine-Learning

Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

Getting-Started-with-Google-BERT

Getting Started with Google BERT, published by Packt

cyber-security

Machine Learning for Network Intrusion Detection & Misc Cyber Security Utilities

NetworkAttackSimulator

An environment for testing AI pentesting agents against a simulated network.

Network-Intrusion-Detection-Using-Machine-Learning

A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach

Network-Intrusion-Detection-Using-Machine-Learning-Techniques

Network intrusions classification using algorithms such as Support Vector Machine (SVM), Decision Tree, Naive Baye, K-Nearest Neighbor (KNN), Logistic Regression and Random Forest.

NSL-KDD-Network-Intrusion-Detection

Machine Learning Algorithms on NSL-KDD dataset

CIDDS

Coburg Intrusion Detection Data Sets

DeepCorr

Payload-Byte

Payload-Byte is a tool for extracting and labeling packet capture (Pcap) files of modern network intrusion detection datasets.

nids-datasets

Download UNSW-NB15 and CIC-IDS2017 Datasets for Network Intrusion Detection (NIDS)

nids-transformers

Tag Generation and Text Generation Inference for Network Packets using Transformers

FML-Network

FLNET2023 is a dataset designed for intrusion detection in Federated Learning scenarios. It's built using the CORE emulator, simulating a realistic network with varied traffic and attacks. It serves as a benchmark for research in federated learning-based intrusion detection.