Ad Fraud Categorization and Detection Methods

This chapter provides a comprehensive review of Ad fraud in three major categories: placement fraud, traffic fraud, and action fraud, which are at different levels of online advertising. Placement fraud mainly focuses on the pages which displaying the Ads. For placement oriented fraudulent activities, they often modify publisher pages or the web pages showing on the users’ devices to increase impressions or clicks. Traffic fraud mainly tries to manipulate the network traffic to inflate the number of impressions generated from individual sites or placements. Action fraud targets users’ meaningful business actions, such as filling an online form or survey, completing an online purchase order, or use users’ previous actions or behaviors to re-target valuable customers. For each type of fraud, we will also review detection methods and approaches for online Ad fraud prevention.

[1]  Ali Jalali,et al.  Real time bid optimization with smooth budget delivery in online advertising , 2013, ADKDD '13.

[2]  Saikat Guha,et al.  Characterizing Large-Scale Click Fraud in ZeroAccess , 2014, CCS.

[3]  Yi Zhu,et al.  Click Fraud , 2009, Mark. Sci..

[4]  Fang Yu,et al.  Knowing your enemy: understanding and detecting malicious web advertising , 2012, CCS '12.

[5]  Foster J. Provost,et al.  Using co-visitation networks for detecting large scale online display advertising exchange fraud , 2013, KDD.

[6]  Yong Guan,et al.  Detecting Click Fraud in Pay-Per-Click Streams of Online Advertising Networks , 2008, 2008 The 28th International Conference on Distributed Computing Systems.

[7]  Lorrie Faith Cranor,et al.  Phinding Phish: An Evaluation of Anti-Phishing Toolbars , 2007, NDSS.

[8]  Jean-Pierre Hubaux,et al.  Online Advertising Fraud , 2011 .

[9]  P. Nowak Deceptibots: when machines go bad , 2012 .

[10]  Chris Kanich,et al.  No Please, After You: Detecting Fraud in Affiliate Marketing Networks , 2015, WEIS.

[11]  Benjamin L. Edelman,et al.  Risk, Information, and Incentives in Online Affiliate Marketing , 2015 .

[12]  Stefan Savage,et al.  Affiliate Crookies: Characterizing Affiliate Marketing Abuse , 2015, Internet Measurement Conference.

[13]  Tyler Moore,et al.  Measuring the Perpetrators and Funders of Typosquatting , 2010, Financial Cryptography.

[14]  Stefan Savage,et al.  Cloak and dagger: dynamics of web search cloaking , 2011, CCS '11.

[15]  Christopher Krügel,et al.  Understanding fraudulent activities in online ad exchanges , 2011, IMC '11.

[16]  Neil Daswani,et al.  The Anatomy of Clickbot.A , 2007, HotBots.

[17]  Paul Barford,et al.  Impression Fraud in On-line Advertising via Pay-Per-View Networks , 2013, USENIX Security Symposium.

[18]  JOHN B. KILLORAN,et al.  How to Use Search Engine Optimization Techniques to Increase Website Visibility , 2013, IEEE Transactions on Professional Communication.

[19]  Divyakant Agrawal,et al.  Using Association Rules for Fraud Detection in Web Advertising Networks , 2005, VLDB.

[20]  S. Savage,et al.  Got traffic?: an evaluation of click traffic providers , 2011, WebQuality '11.

[21]  Mauro Conti,et al.  TRAP: Using Targeted ads to unveil Google personal profiles , 2015, 2015 IEEE International Workshop on Information Forensics and Security (WIFS).

[22]  Tamara Dinev,et al.  Why spoofing is serious internet fraud , 2006, CACM.

[23]  Bobji Mungamuru,et al.  Competition and Fraud in Online Advertising Markets , 2008, Financial Cryptography.

[24]  Yuhui Zheng,et al.  Image segmentation by generalized hierarchical fuzzy C-means algorithm , 2015, J. Intell. Fuzzy Syst..

[25]  Wei Meng,et al.  Understanding Malvertising Through Ad-Injecting Browser Extensions , 2015, WWW.

[26]  Ramesh Govindan,et al.  AdReveal: improving transparency into online targeted advertising , 2013, HotNets.

[27]  Tong Zhang,et al.  Crowd Fraud Detection in Internet Advertising , 2015, WWW.

[28]  Vern Paxson,et al.  Ad Injection at Scale: Assessing Deceptive Advertisement Modifications , 2015, 2015 IEEE Symposium on Security and Privacy.

[29]  Benjamin Edelman Accountable? The Problems and Solutions of Online Ad Optimization , 2014, IEEE Security & Privacy.

[30]  Hsinchun Chen,et al.  A Comparison of Tools for Detecting Fake Websites , 2009, Computer.

[31]  Nathaniel Good,et al.  Behavioral Advertising: The Offer You Can't Refuse , 2012 .

[32]  Richard J. Enbody,et al.  Malvertising – exploiting web advertising , 2011 .