在这里汇总工作中阅读过的广告反作弊相关论文、参考资料。除少数几篇论文外，其它所有资料都是以链接的形式提供。广告反作弊在各个公司都是一个很神秘的模块，公开的资料比较少。希望这里的整理可以给相关技术人员提供便利。另外，也会收集一些其它领域，比如金融、电商等行业的反作弊论文，希望它山之石可以攻玉，给广告反作弊提供不一样的思路。
如果对广告反作弊领域感兴趣，欢迎和我讨论，我的联系方式如下：
- email: xinyu.wang1@gmail.com
- 知乎: 王新宇的知乎
- 微信:
- The Lane’s Gifts v. Google Report by Alexander Tuzhilin. 2006. Note
- Click Fraud Detection: Adversarial Pattern Recognition over 5 Years at Microsoft by Brendan Kitts et al. Real World Data Mining Applications 2015.
- Fighting Online Click-Fraud Using Bluff Ads by Hamed Haddadi. ACM Computer Communication Review 2010. Note
- Measuring and Fingerprinting Click-Spam in Ad Networks by Vacha Dave et al. ACM SIGCOMM Conference on Data Communication 2012.
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- A Novel Approach Based on Ensemble Learning for Fraud Detection in Mobile Advertising by Kasun S. Perera et al. International Workshop on Fraud Detection in Mobile Advertising (FDMA) 2012. Note
- Hybrid Models for Click Fraud Detection in Mobile Advertising by Chen Wei et al. International Workshop on Fraud Detection in Mobile Advertising (FDMA) 2012.
- Random Forests for the Detection of Click Fraud in Online Mobile Advertising by Daniel Berrar et al. International Workshop on Fraud Detection in Mobile Advertising (FDMA) 2012.
- Hierarchical Committee Machines for Fraud Detection in Mobile Advertising by S. Shivashankar et al. International Workshop on Fraud Detection in Mobile Advertising (FDMA) 2012.
- FDMA 2012 Competition Dataset by BuzzCity Pte. Ltd. FDMA 2012.
- 2017广告反欺诈白皮书 by 腾讯灯塔, 秒针, AdMaster. 2017.
- The State of Mobile Fraud Q1 2018 by Appsflyer. 2018.
- 2020**移动广告反欺诈白皮书 by 腾讯安全天御, 腾讯防火墙, InMobi. 2020.
- 阿里妈妈流量反作弊算法实践 by 阿里妈妈风控团队. 2021.
- Anomaly Detection: A Survey by Varun Chandola et al. ACM Computing Surveys, Vol. 41, No. 3, 15, 01.07.2009.
- Scikit-learn Novelty and Outlier Detection
- Python Outlier Detection (PyOD)
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- APATE: A Novel Approach for Automated Credit Card Transaction Fraud Detection using Network-Based Extensions by Veronique Van Vlasselaer et al. Decision Support Systems, 2015.
- Detecting Fraudulent Behavior Using Recurrent Neural Networks by Yoshihiro Ando et al. Computer Security Symposium 2016.
- Session-Based Fraud Detection in Online E-Commerce Transactions Using Recurrent Neural Networks by Shuhao Wang et al. PKDD 2017. Slides
- 2017电子商务生态安全白皮书 by 电子商务生态安全联盟. 2017.