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
250 stars
6 watching
53 forks
Language: Python
last commit: almost 4 years agoLinked from 1 awesome list
dataminingdeep-learningfraud-detectionfraud-preventiongraphneuralnetworkmachine-learningreinforcement-learningsecurity
benedekrozemberczki/awesome-fraud-detection-papersRelated projects:
| Repository | Description | Stars |
|---|---|---|
 safe-graph/dgfraud | A toolbox for building and comparing graph neural network-based fraud detection models | 698 |
| 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 | 131 |
 zhao-tong/graph-anomaly-loss | This repository provides code for training a model to detect anomalies in graph data using pattern mining and feature learning. | 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 | 137 |
 iloveai2019/ocan | A framework for detecting fraud using a novel neural network approach that learns from benign user data | 24 |
 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. | 1,046 |
 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. | 875 |
 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 |