fraud-detection

There are 793 repositories under fraud-detection topic.

  • fingerprintjs

    fingerprintjs/fingerprintjs

    Browser fingerprinting library. Accuracy of this version is 40-60%, accuracy of the commercial Fingerprint Identification is 99.5%. V4 of this library is BSL licensed.

    Language:TypeScript21.1k4175492.2k

  • yzhao062/pyod

    A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

    Language:Python8k1473291.3k

  • yzhao062/anomaly-detection-resources

    Anomaly detection related books, papers, videos, and toolboxes

    Language:Python8k286221.7k

  • MISP/MISP

    MISP (core software) - Open Source Threat Intelligence and Sharing Platform

    Language:PHP5k2746.4k1.3k
  • awesome-fraud-detection-papers

    benedekrozemberczki/awesome-fraud-detection-papers

    A curated list of data mining papers about fraud detection.

    Language:Python1.6k753297

  • safe-graph/graph-fraud-detection-papers

    A curated list of graph-based fraud, anomaly, and outlier detection papers & resources

    1.3k534241
  • pygod

    pygod-team/pygod

    A Python Library for Graph Outlier Detection (Anomaly Detection)

    Language:Python1.2k1659125

  • InQuest/ThreatIngestor

    Extract and aggregate threat intelligence.

    Language:Python79541100132
  • MIDAS

    Stream-AD/MIDAS

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

    Language:C++755291892

  • Ullaakut/astronomer

    A tool to detect illegitimate stars from bot accounts on GitHub projects

    Language:Go68363825

  • gwillem/magento-malware-scanner

    Scanner, signatures and the largest collection of Magento malware

    Language:HTML6738250159

  • safe-graph/DGFraud

    A Deep Graph-based Toolbox for Fraud Detection

    Language:Python6711513159

  • t4d/StalkPhish

    StalkPhish - The Phishing kits stalker, harvesting phishing kits for investigations.

    Language:Python609273881

  • Fraud-Detection-Handbook/fraud-detection-handbook

    Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook

    Language:Jupyter Notebook444205159

  • Faceplugin-ltd/FaceRecognition-LivenessDetection-Android

    Face Recognition Face Liveness Detection Android SDK (Face Detection, Face Landmarks, Face Anti Spoofing, Face Pose, Face Expression, Eye Closeness, Age, Gender and Face Recognition)

    Language:Java37110146

  • blackdotsh/getIPIntel

    IP Intelligence is a free Proxy VPN TOR and Bad IP detection tool to prevent Fraud, stolen content, and malicious users. Block proxies, VPN connections, web host IPs, TOR IPs, and compromised systems with a simple API. GeoIP lookup available.

    Language:PHP310271752

  • XiaoxiaoMa-MQ/Awesome-Deep-Graph-Anomaly-Detection

    Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors and boost further research in this area.

    3026047

  • IBM/TabFormer

    Code & Data for "Tabular Transformers for Modeling Multivariate Time Series" (ICASSP, 2021)

    Language:Python301102979

  • jacopotagliabue/MLSys-NYU-2022

    Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022

    Language:Jupyter Notebook2916024

  • sublime-security/emailrep.io

    emailrep.io Public API

    282151231

  • awslabs/fraud-detection-using-machine-learning

    Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker

    Language:Jupyter Notebook265198146

  • talsec/Free-RASP-Community

    SDK providing app protection and threat monitoring for mobile devices, available for Flutter, Cordova, Android and iOS.

    24871111

  • IBM/AMLSim

    The AMLSim project is intended to provide a multi-agent based simulator that generates synthetic banking transaction data together with a set of known money laundering patterns - mainly for the purpose of testing machine learning models and graph algorithms. We welcome you to enhance this effort since the data set related to money laundering is critical to advance detection capabilities of money laundering activities.

    Language:Python241246181

  • MiniAiLive/FaceLivenessDetection

    Upgrade your Android app with MiniAiLive's 3D Passive Face Liveness Detection! With our advanced computer vision techniques, you can now enhance security and accuracy on your Android platform. Check out our latest repository containing a demonstration of 2D & 3D passive face liveness detection capabilities. Try it out today!

    Language:Kotlin237167

  • YingtongDou/CARE-GNN

    Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

    Language:Python23351451

  • selimfirat/pysad

    Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)

    Language:Python2235620

  • IPL/fraud-detection-papers

    A collection of research and survey papers of fraud detection mainly in advertising.

    22219041

  • fzliu/radient

    Radient turns many data types (not just text) into vectors for similarity search, clustering, regression analysis, and more.

    Language:Python2207

  • januusio/cryptowallet_risk_scoring

    A free cryptowallet risk scoring tool with fully explainable scoring.

    Language:Python2209656

  • t4d/PhishingKitHunter

    Find phishing kits which use your brand/organization's files and image.

    Language:Python21916164

  • trustdecision/trustdevice-ios

    Leading open source version of iOS device fingerprint, accurate deviceID and risk identification.

    Language:Objective-C2104112

  • awslabs/realtime-fraud-detection-with-gnn-on-dgl

    An end-to-end blueprint architecture for real-time fraud detection(leveraging graph database Amazon Neptune) using Amazon SageMaker and Deep Graph Library (DGL) to construct a heterogeneous graph from tabular data and train a Graph Neural Network(GNN) model to detect fraudulent transactions in the IEEE-CIS dataset.

    Language:TypeScript205213139

  • GitiHubi/deepAI

    Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

    Language:Jupyter Notebook19516381
  • SentryPeer

    SentryPeer/SentryPeer

    Protect your SIP Servers from bad actors at https://sentrypeer.org

    Language:C150121817

  • milcent/benford_py

    Python implementation of Benford's Law tests.

    Language:Jupyter Notebook149134351

  • juzstu/TianCheng

    甜橙金融初赛Rank1

    Language:Python1364448