There are 2 repositories under detect-anomalies topic.
Tidy anomaly detection
Hastic data management server for labeling patterns and anomalies in Grafana
Scripts to help to detect anomalies in pcap file. Anomaly Detection using tensorflow and tshark.
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.
Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System.
A machine learning approach to machine anomaly detection on the MIMII dataset.
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.
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.
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!
Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning, Recurrent Neural Network models, MERN web I/O System.
Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System.
This repo depicts the techniques I have tried to detect anomalies in a dataset.
Contains an implementation using NuPIC HTM model for Network Anomaly Detection. This uses the Hierarchical Temporal Memory Architecture to detect anomalies in networks.
Data Mining Web Application to Identify Anomalies in Public Procurement Rating Parameters
A tool to detect anomalies in time-series.
These are the scripts I used at my summer school at IIT BHU for image processing and anomaly detection.