The most advanced open-source browser fingerprinting library
Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!
MISP (core software) - Open Source Threat Intelligence and Sharing Platform
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
A curated list of data mining papers about fraud detection.
A curated list of graph-based fraud, anomaly, and outlier detection papers & resources
Face Recognition, Face Liveness Detection, Face Anti-Spoofing, Face Detection, Face Landmarks, Face Compare, Face Matching, Face Pose, Face Expression, Face Attributes, Face Templates Extraction, Face Landmarks
Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook
Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker
A Deep Graph-based Toolbox for Fraud Detection
Scanner, signatures and the largest collection of Magento malware
A Python Library for Graph Outlier Detection (Anomaly Detection)
Extract and aggregate threat intelligence.
Liveness detection SDK iOS- iBeta level 2 certified 3D passive liveness detection engine which can detect printed photos, video replay, 3D masks, and deepfake threats
A data science project to predict whether a transaction is a fraud or not.
3D Passive Face Liveness Detection! Supports Face Detection, Face Matching, Face Analysis, Face Sentiment, Face Alignment, Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution on Android
Open security analytics. Understand, monitor, and protect your product from cyber threats, account takeovers, bots, and abuse.
Anomaly Detection on Dynamic (time-evolving) Graphs in Real-time and Streaming manner. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.
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 …
Code & Data for "Tabular Transformers for Modeling Multivariate Time Series" (ICASSP, 2021)
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