Top 160 anomaly-detection open source projects

RNN based Time-series Anomaly detector model implemented in Pytorch.

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

A toolkit for automated log parsing [ICSE'19, TDSC'18, DSN'16]

A Python toolkit for rule-based/unsupervised anomaly detection in time series

Anomaly Detection on Dynamic (time-evolving) Graphs in Real-time and Streaming manner. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

A large collection of system log datasets for AI-powered log analytics

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

WinDBG Anti-RootKit Extension

Anomaly detection related books, papers, videos, and toolboxes

An Integrated Experimental Platform for time series data anomaly detection.

Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data

Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

Anomaly detection implemented in Keras

Luminaire is a python package that provides ML driven solutions for monitoring time series data.

A PyTorch implementation of the Deep SVDD anomaly detection method

Official implementation of Paper Future Frame Prediction for Anomaly Detection -- A New Baseline, CVPR 2018

Anomaly detection

Hastic data management server for analyzing patterns and anomalies from Grafana

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Python module for hyperspectral image processing

Machine Learning Lectures at the European Space Agency (ESA) in 2018

A Deep Graph-based Toolbox for Fraud Detection

Tidy anomaly detection

An open-source, low-code machine learning library in Python

This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning.

Contains the thorough experiments made for a FloydHub article on Anomaly Detection

Merlion: A Machine Learning Framework for Time Series Intelligence

Thio - a playground for real-time anomaly detection

SyntheticSun is a defense-in-depth security automation and monitoring framework which utilizes threat intelligence, machine learning, managed AWS security services and, serverless technologies to continuously prevent, detect and respond to threats.

A thesis submitted for the degree of Master of Science in Computer Networks and Security

This repository is the PyTorch implementation of GAN Ensemble for Anomaly Detection.

(Python, R, C++) Explainable outlier/anomaly detection through decision tree conditioning

Unsupervised Anomaly Detection with Generative Adversarial Networks on MIAS dataset

Useful Toolbox for Anomaly Detection

High-performance time series algorithms for Ruby

Faster and more precisely than Grad-CAM

使用极端值理论(Extreme Value Theory)实现阈值动态自动化设置

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Official codes for CVPR2021 paper "MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection"

Supplementary material for KDD 2018 workshop "DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles"

ADRepository: Real-world anomaly detection datasets

Benchmark for DeepLearning anomaly detection

OpenSnitch is a GNU/Linux application firewall

A repository for code accompanying the manuscript 'An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series' (published at TNNLS)

An R package for space-time anomaly detection using scan statistics.

Deploying a Batch Scoring Pipeline for Python Models

Anomaly Detection on Time-Evolving Streams in Real-time. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

Implementation of the famous Image Manipulation\Forgery Detector "ManTraNet" in Pytorch

benfordslaw is about the frequency distribution of leading digits.

Resources for working with time series and sequence data

Digital Cell Sorter (DCS): single cell RNA-seq analysis toolkit. Documentation:

⭐ An anomaly-based intrusion detection system.

Threat Detection & Anomaly Detection rules for popular open-source components

fast implementation of singular spectrum transformation (change point detection algorithm)

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection

anomaly detection with anomalize and Google Trends data