gcamfer / Anomaly-ReactionRLLinks
Using RL for anomaly detection in NSL-KDD
☆120Updated 2 years ago
Alternatives and similar repositories for Anomaly-ReactionRL
Users that are interested in Anomaly-ReactionRL are comparing it to the libraries listed below
Sorting:
- Repository for IEEE CCNC'21 paper titled "Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural Network".☆46Updated 2 years ago
- Intrusion Detection System using Deep Reinforcement Learning and Generative Adversarial Networks☆46Updated 11 months ago
- Reinforcement Learning for Anomaly Detection☆45Updated 7 years ago
- Network intrusion detection with Machine Learning (Deep Learning) experiment : 1d-cnn, softmax, neural networks, convolution☆47Updated last year
- Our implementations of the flow-based network intrusion detection model (for the COMNET paper)☆46Updated 5 years ago
- PySpark solution to the NSL-KDD dataset: https://www.unb.ca/cic/datasets/nsl.html☆126Updated 4 years ago
- A GAN-based model focused on anomaly detection in discrete dataset☆26Updated 5 years ago
- [ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection☆166Updated 2 years ago
- Cyber-attack classification in the network traffic database using NSL-KDD dataset☆26Updated 4 years ago
- Using PyTorch to train kddcup99 dataset with convolutional neural networks.☆54Updated 6 years ago
- Basic Machine learning projects and assignments done by me.☆32Updated 5 years ago
- Pytorch implementation of LuNet: A Deep Neural Network for Network Intrusion Detection☆52Updated 5 years ago
- Here, we use RNN to deal with the network intrusion problem. The UNSW-NB15 dataset is used.☆72Updated 4 years ago
- Paper Implementation☆27Updated last year
- manojkumar-github / Intrusion-Detection-System-for-IoT-networks-using-Gated-Recurrent-Neural-Networks-GRUAn Intelligent Intrusion Detection System for IoT networks using Gated Recurrent Neural Networks (GRU) : A Deep Learning Approach☆33Updated 7 years ago
- I have tried some of the machine learning and deep learning algorithm for IDS 2017 dataset. The link for the dataset is here: http://www.…☆41Updated 6 years ago
- Two staged IDS specific to IoT networks where Signature based IDS and Anomaly based IDS which is trained and classified using machine lea…☆45Updated 6 years ago
- ☆21Updated 4 years ago
- Apply modern, deep learning techniques for anomaly detection to identify network intrusions.☆50Updated 8 months ago
- ramyaelineni5 / ML-based-Network-Intrusion-Detection-using-Cyber-Dataset-CSE-CIC-IDS2018-to-classify-network-attacks☆43Updated 4 years ago
- Attention Model for Network Intrusion Detection☆18Updated 6 years ago
- 这是一个封装了KDDCup99、NSL-KDD、UNSW-NB15等入侵监测数据集的Python包。☆47Updated 5 years ago
- A research project of anomaly detection on dataset IoT-23☆100Updated 11 months ago
- Intrusion Detection System using Machine Learning and Deep Learning☆88Updated last year
- This repository consists of python codes that performs attack classification based on the KDD and CIDDS dataset using CNN, LSTM-RNN and H…☆23Updated 2 years ago
- CICIDS2017 dataset☆71Updated 3 years ago
- This repository contains a notebook implementing an autoencoder based approach for intrusion detection, the full documentation of the stu…☆32Updated 6 years ago
- Machine Learning with the NSL-KDD dataset for Network Intrusion Detection☆263Updated 5 years ago
- ☆24Updated 6 years ago
- Implement a VAE to learn a reduced state space representation from the NSL-KDD dataset, capturing essential features of normal network t…☆13Updated last year