zhao-cai Goto Github PK

adaptive-structural-fingerprint

awesome-cs-books

经典编程书籍大全，涵盖：计算机系统与网络、系统架构、算法与数据结构、前端开发、后端开发、移动开发、数据库、测试、项目与团队、程序员职业修炼、求职面试等

blockchain-tutorial

cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

ensemblelearning

包括决策树和随机森林进行离职人员预测，Xgboost和lightGBM的应用

ethereum_graph_analysis

node2vec

ocgnn

my implement of my paper

ocsvm-anomaly-detection

anomaly detection by one-class SVM

one-class-svm

credit card anomaly testing using One Class SVM

phishing-detection-on-ethereum

As the most famous application of blockchain, cryptocurrency has suffered huge economic losses due to phishing scams. Our work shares phishing account information from Etherscan and the code for how to crawl it. In addition, the trans2vec algorithm for detection was shared. In our work, accounts and transactions in Ethereum are treated as nodes and edges, so detection of phishing accounts can be modeled as a node classification problem. This work starts from Etherscan exposed nodes reported by phishing points and randomly extracts the same number of non-phishing fraud nodes. A large Ethereum trading network was crawled from ethereum records through breadth search.

phishing_detection

pygat

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

sz100-01

sz100-02

sz100-03

wgcn_graph-convolutional-networks-with-weighted-structural-features

WGCN: Graph Convolutional Networks with Weighted Structural Features, SIGIR 2021