cloudera / CML_AMP_Anomaly_DetectionLinks
Apply modern, deep learning techniques for anomaly detection to identify network intrusions.
☆49Updated 6 months ago
Alternatives and similar repositories for CML_AMP_Anomaly_Detection
Users that are interested in CML_AMP_Anomaly_Detection are comparing it to the libraries listed below
Sorting:
- GAN / AUTOENCODER for network intrusion detection using NSL-KDD dataset: https://www.kaggle.com/datasets/hassan06/nslkdd☆18Updated 2 years ago
- Application of novel EC-GAN method on Network Intrusion Detection☆21Updated 3 years ago
- This project is an open-source project based on a GAN network anomaly detection.☆13Updated 10 months ago
- Network intrusion detection with Machine Learning (Deep Learning) experiment : 1d-cnn, softmax, neural networks, convolution☆46Updated last year
- 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
- Generative adversarial networks for Network Intrusion Benchmark datasets☆35Updated 10 months ago
- Code for the paper "Anomaly-Based Intrusion Detection in IIoT Networks Using Transformer Models"☆33Updated 2 years ago
- Pre-processing NSL-KDD dataset using Data mining techniques. Algorithm written in python to detect the attacks in NSL KDD dataset.☆26Updated 5 years ago
- A research project of anomaly detection on dataset IoT-23☆99Updated 9 months ago
- A GAN-based model focused on anomaly detection in discrete dataset☆26Updated 5 years ago
- Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset☆173Updated 3 years ago
- Here, we use RNN to deal with the network intrusion problem. The UNSW-NB15 dataset is used.☆72Updated 4 years ago
- 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 6 years ago
- Building an Intrusion Detection System on UNSW-NB15 Dataset Based on Machine Learning Algorithm☆85Updated 4 years ago
- IoT intrusion Detection Model based on neural network and random forests☆46Updated 6 years ago
- Detection of network traffic anomalies using unsupervised machine learning☆26Updated 3 years ago
- ☆24Updated 6 years ago
- Cyber-attack classification in the network traffic database using NSL-KDD dataset☆26Updated 4 years ago
- A Recurrent Neural Networks implementation using Keras for network intrusion detection☆30Updated 4 years ago
- convGRU based autoencoder for unsupervised & spatial-temporal anomaly detection in computer network (PCAP) traffic.☆17Updated last year
- Two staged IDS specific to IoT networks where Signature based IDS and Anomaly based IDS which is trained and classified using machine lea…☆43Updated 6 years ago
- Intrusion Detection System using Deep Reinforcement Learning and Generative Adversarial Networks☆44Updated 9 months ago
- Payload-Byte is a tool for extracting and labeling packet capture (Pcap) files of modern network intrusion detection datasets.☆38Updated 11 months ago
- We use attention model for intrusion detection. The idea of Hierarchical Attention Model for Intrusion Detection comes from the applicat…☆12Updated 4 years ago
- This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets☆55Updated 5 years ago
- Anomaly based Instrusion Detection System using RNN-LSTMs. Datasets include NSL-KDD and UNSW-NB15.☆35Updated 4 years ago
- A project using Django, sklearn and pandas to detect anomalies in network traffic using machine learning☆45Updated 3 years ago
- Network related services, programs and applications are developing greatly, however, network security breaches are also developing with t…☆23Updated 3 years ago
- A network data classifier for UNSW-NB15 data set. This is an university course work for "ITKST42 Information Security Technology".☆38Updated 8 years ago
- This repository presents the implemetation of a highly optimized Deep Transfer Learning (DTL) and Genetic Algorithm (GA) based intrusion …☆16Updated last year