jiajia5201314

jiajia5201314's Stars

• MA-YuS/anomaly-detection

  Abnormal detection of energy consumption data of subway electromechanical equipment

  Language:Python1

• FengLei717/Abnormal_order_detection_of_e-commerce

  该数据源2018年在gitee被公开，是**某500强企业在2013年电商交易的真实信息数据，数据中标注了异常订单，可以根据已有数据来预测订单是否为异常订单，来为企业的业务提供预警

  Language:Jupyter Notebook11

• pandahuang/BankTransAbnormalDetection

  Data mining program for detect abnormal bank transactions from raw data.

  Language:Python2

• DDJeri/AbnormalFlowDetection

  Language:Java21

• ChengChen-Steven/Fraud-Detection-Credit-Card-Account-Origination

  This project commissions to examine the 100,000 credit card application data, detect abnormality and potential fraud in the dataset. All data manipulation and analysis are conducted in R. Featured analysis methods include Principal Component Analysis (PCA), Heuristic Algorithm and Autoencoder.

  Language:R84

• wobiskai/anomaly-detection-in-Bitcoin

  Detect abnormal transactions in Bitcoin data

  Language:Jupyter Notebook63

• Battlingboy/AE-IDS

  Network Intrusion Detection System(Abnormal Detection)

  Language:Python116

• chenxu93/abnormal-traffic

  IDS abnormal traffic detection tensorflow

  Language:Python3716

• Mphasis-ML-Marketplace/Financial-Transactions-Fraud-Detection

  This solution is a deep learning based algorithm capable of training on transactional data, to identify spurious transactions.

  Language:Jupyter Notebook1

• Jehuty4949/NSL_KDD

  NSL-KDD Dataset

  172115

• PowerLZY/MalGAN

  主题为”基于GAN的恶意软件对抗样本生成“。首先介绍了恶意软件发展现状，引出基于模式匹配、特征空间和问题空间三种方式去检测恶意软件。然后介绍了如何生成对抗样本攻击恶意软件检测器，详细介绍了基于GAN的恶意软件对抗样本的MalGAN框架，并对实验结果进行了对比。最后总结了结构性对抗样本的约束：可用转换 、保留语义、似然性、副作用特征。

  Language:Python316

• xiaoyu2018/QuantumCnn-NetworkAttackDetection

  修改谷歌提供的样例量子卷积神经网络模型，基于KDD99数据集进行训练，实现了网络攻击分类检测。

  Language:Python322

• lxyeternal/WAF

  基于机器学习的web攻击检测系统

  Language:Python5918

• XFR1998/CCF-BDCI2022-Web-Attack-Detection-and-Classification

  此仓库代码为本人参加的CCF-BDCI-2022 赛道：Web攻击检测与分类识别 (多分类任务)，比赛rank-23。队员：Furen Xu

  Language:Jupyter Notebook133

• Mamcose/NSL-KDD-Network-Intrusion-Detection

  Machine Learning Algorithms on NSL-KDD dataset

  Language:Jupyter Notebook8642

• CynthiaKoopman/Network-Intrusion-Detection

  Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

  Language:Jupyter Notebook23893

• Designlotus/Anti-fraud-prediction-model

  交易欺诈作为信用卡行业面临的主要贷后风险业务问题，每年都使信用卡行业遭受巨额损失。基于大数据机器学习开发出高效的交易欺诈识别模型一直是金融行业的主要挑战之一。本次大赛以此作为主题

  Language:Jupyter Notebook3819

• baoyunfan0101/AbnormalAccountsRecognition

  依据账户数据识别涉及交易欺诈的风险账户。

  Language:Python3

• ZongXR/DCIC2023-Fraud-Risk-Identification

  本赛题旨在运用有效的金融科技和大数据系统，分析涉赌涉诈资金交易新方式，持续优化风险监测模型，通过赛题提供的涉赌涉诈黑名单、白名单及用于训练的相关交易流水数据集，构建涉赌涉诈账户算法识别模型，全面排查存量风险。A榜排名11/1594，B榜排名13/1594。

  Language:Jupyter Notebook3916

• buhuixiezuowendelihua/Anomaly-Detection

  异常值检测算法总结

  Language:Jupyter Notebook16222

• kunlaotou/Anomaly-Detection

  异常检测

  Language:Python15652

• hy330456/tianchi_antispam

  第三届 Apache Flink 极客挑战赛暨AAIG CUP——电商推荐“抱大腿”攻击识别

  Language:Python1

• rickyxume/TianChi_RecSys_AntiSpam

  第三届 Apache Flink 极客挑战赛暨AAIG CUP——电商推荐“抱大腿”攻击识别亚军代码方案

  Language:Python2817