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: [email protected]
• 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.

• DECAF: Detecting and Characterizing Ad Fraud in Mobile Apps by Bin Liu et al. Proc. 11th USENIX Conf. Netw. Syst. Des. Implementation 2014.
• MAdFraud: Investigating Ad Fraud in Android Applications by Jonathan Crussell et al. Proc. 12th International Conference on Mobile Systems Applications and Services (MobiSys'14) 2014.

• Detecting Click Fraud in Pay-Per-Click Streams of Online Advertising Networks by Linfeng Zhang et al. ICDCS 2008.

• Using Association Rules for Fraud Detection in Web Advertising Networks by Ahmed Metwally et al. VLDB 2005.

• Detecting Click Fraud in Online Advertising: A Data Mining Approach by Richard Oentaryo et al. JMLR 2014.
• Feature Engineering for Click Fraud Detection by Clifton Phua et al. International Workshop on Fraud Detection in Mobile Advertising (FDMA) 2012.
• 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.

• 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)
• ELKI: Environment for Developing KDD-Applications Supported by Index-Structures

• Facebook Immune System by Tao Stein et al. Proceedings of the 4th Workshop on Social Network Systems, SNS, 2011.

• Learned lessons in credit card fraud detection from a practitioner perspective by A Dal Pozzolo et al. Expert Systems with Applications, 41(10):4915–4928, 2014.
• 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.

• 收集汇总不同行业不同公司，网络上公开的风控或安全的架构、方案、算法
• 收录风控领域相关算法Paper