GitHub topics: detect-anomalies

Repositories

Shaik-Sohail-72/Network-Intrusion-Detection-Using-Deep-Learning

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System.

Language: EJS - Size: 19.4 MB - Last synced at: 9 days ago - Pushed at: over 1 year ago - Stars: 40 - Forks: 16

MohdSaif-1807/Network-Intrusion-Detection-System-Using-Machine-Learning-and-Deep-Learning

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System. The deployed project link is as follows.

Language: EJS - Size: 11.2 MB - Last synced at: 19 days ago - Pushed at: 12 months ago - Stars: 16 - Forks: 2

business-science/anomalize

Tidy anomaly detection

Language: R - Size: 41.9 MB - Last synced at: 12 days ago - Pushed at: over 1 year ago - Stars: 339 - Forks: 61

H21lab/Anomaly-Detection

Scripts to help to detect anomalies in pcap file. Anomaly Detection using tensorflow and tshark.

Language: Jupyter Notebook - Size: 1.79 MB - Last synced at: 15 days ago - Pushed at: almost 5 years ago - Stars: 81 - Forks: 21

hastic-zzz/hastic-grafana-app

Hastic data management server for labeling patterns and anomalies in Grafana

Language: TypeScript - Size: 1.35 MB - Last synced at: 13 days ago - Pushed at: over 3 years ago - Stars: 180 - Forks: 16

AmberSJones/pyhydroqc

This software was designed with the purpose of anomaly detection and correction for time series water sensor data. This software was developed using the Logan River Observatory data set.

Language: HTML - Size: 45.6 MB - Last synced at: 18 days ago - Pushed at: about 2 years ago - Stars: 22 - Forks: 11

Central-Cee/-Network-Intrusion-Detection-System-

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System.

Language: Python - Size: 11.1 MB - Last synced at: 10 months ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0

HawkPhantom/unsupervised-anomaly-detection

A tool to detect anomalies in time-series.

Language: Python - Size: 7.81 KB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

shubhammola/NIDS

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning, Recurrent Neural Network models, MERN web I/O System.

Language: EJS - Size: 13.2 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 1

Ellie190/Anomalies-in-Public-Procurement

Data Mining Web Application to Identify Anomalies in Public Procurement Rating Parameters

Language: R - Size: 2.93 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 1

eaglewarrior/Anomaly-Detection

This repo depicts the techniques I have tried to detect anomalies in a dataset.

Language: Jupyter Notebook - Size: 1.89 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

DRTorresRuiz/AnomalyDetection 📦

We are detecting anomalies in the temperature using Markov chain. Working with python

Language: Python - Size: 150 KB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 2 - Forks: 2

bhanukaManesha/brain-inspired-user-behavioural-traffic-monitoring-system 📦

Contains an implementation using NuPIC HTM model for Network Anomaly Detection. This uses the Hierarchical Temporal Memory Architecture to detect anomalies in networks.

Language: Python - Size: 53 MB - Last synced at: almost 2 years ago - Pushed at: almost 5 years ago - Stars: 1 - Forks: 0

BA-HanseML/NF_Prj_MIMII_Dataset

A machine learning approach to machine anomaly detection on the MIMII dataset.

Language: Jupyter Notebook - Size: 164 MB - Last synced at: almost 2 years ago - Pushed at: almost 5 years ago - Stars: 17 - Forks: 4

HamishWoodrow/anomaly_detection

This is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.

Language: Jupyter Notebook - Size: 416 KB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 61 - Forks: 20

sergiovirahonda/AnomalyDetection

This repository is part of an article about how to forecast and detect anomalies on time-series data. The main objective is to train a RNN regressor on the Bitcoin dataset to predict future values on then detect anomalies in the whole data window - that last step achieved by implementing a RNN Autoencoder. You'll see some other models in the notebooks that I've provided to you in case they are of your interest and this RNN regressor + RNN Autoencoder doesn't perform well for your purpose in any other scenario. The dataset used is available at https://www.kaggle.com/mczielinski/bitcoin-historical-data and contains BITCOIN/USD 1-minute candle data, from 2012-01-01 to 2020-12-31. I hope you can get advantage of this approach!

Language: Jupyter Notebook - Size: 17.5 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 9 - Forks: 7