CARE-GNN

Fraud Detector

An implementation of a graph neural network-based fraud detector designed to counter camouflaged fraudsters

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

GitHub

246 stars
6 watching
53 forks
Language: Python
last commit: about 2 years ago
Linked from 1 awesome list

dataminingdeep-learningfraud-detectionfraud-preventiongraphneuralnetworkmachine-learningreinforcement-learningsecurity

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
safe-graph/dgfraud A toolbox for building and comparing graph neural network-based fraud detection models 693
yingtongdou/nash-detect An algorithm for detecting spam reviews using reinforcement learning to train robust detectors against strategically synthesized attacks. 118
safe-graph/ugfraud A toolbox for unsupervised graph-based fraud detection using multiple algorithms and techniques 129
zhao-tong/graph-anomaly-loss A software package for detecting anomalies in graphs by learning patterns and features 40
yuwenxiong/py-r-fcn An implementation of R-FCN, an object detection algorithm using region-based fully convolutional networks. 1,048
xiang-wuu/ncnn-android-yolov7 An Android implementation of object detection using Yolov7 and the ncnn neural network library 133
iloveai2019/ocan A framework for detecting fraud using a novel neural network approach that learns from benign user data 23
ijkguo/mx-rcnn An implementation of Faster R-CNN using MXNet for object detection tasks 671
xiaolonw/adversarial-frcnn A Caffe-based implementation of A-Fast-RCNN, a method for object detection using adversarial networks. 482
zhaoweicai/cascade-rcnn An object detection framework that combines multiple popular algorithms in a multi-stage process to improve detection accuracy. 1,043
yknzhu/segdeepm A tool for fine-tuning deep neural networks to improve object detection and segmentation capabilities by incorporating contextual information. 27
panpanzheng/safe Develops a survival analysis-based model to detect fraud early 34
charlesshang/tffrcnn A TensorFlow-based implementation of Faster R-CNN object detection using pre-trained ResNet networks and custom datasets. 874
roytsai27/dual-attentive-tree-aware-embedding Develops a machine learning model to classify and rank customs fraud cases based on transaction-level data and tree-based features 61
feigechuanshu/ncnn-android-yolov6 An Android implementation of YOLOv6 object detection using the ncnn library and OpenCV for efficient mobile deployment 62