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The
Digital Ad Fraud Ecosystem
October 2015
Augustine Fou, PhD.
acfou [at] mktsci. com
212. 203. 7239
October 2015 / Page 1marketing.scienceconsulting group, inc.
Dr. Augustine Fou
Fraud siphons 1/3 of dollars out of ad ecosystem
Advertisers
“ad spend” in digital
is $56B in 2015
Publishers
are left with only
2/3 of the dollars
Bad Guys
siphon 1/3 of ad spend
OUT of the ecosystem
• Ad dollars are being siphoned OUT of the ecosystem into the pockets of the bad guys
• Advertisers have lower ROI due to fraud (fake impressions/clicks, non-humans/bots)
• Publishers have lower revenues (ad dollars stolen by bad guys)
2/3
1/3
Users
use ad blocking and
need to protect privacy
October 2015 / Page 2marketing.scienceconsulting group, inc.
Dr. Augustine Fou
Bad guys have a whole ecosystem; make money at every point
Advertisers
“ad spend” in digital
is $56B in 2015
Publishers
are left with only
2/3 of the dollars
“Farmers”
Hackers whose job it is to
get malware on computers,
so botnets can be created.
2/3
1/3
Piracy/Porn Sites
Sites that attract real human
visitors in order to attempt
to plant malware on PCs.
Fake Sites
Sites with fake content,
created solely to carry ads
(display, video, search)
Fake Visitors/Bots
Bots that hit webpages to
cause ad impressions, click
on ads, collect cookies.
Sourced Traffic
Unknown users from
unknown places that can be
purchased for low CPMs
Audience Extension
Attracting audiences
through related content
which launders origins.
Fake Accounts
Fake Facebook, Twitter,
LinkedIn, etc. accounts used
to gather data/compromise
Ad Network
Network willing to look the
other way because they get
a cut of the payout
Data Management
Fake or falsified data to
launder or cover up fraud;
also command premiums
fraud ecosystem
October 2015 / Page 3marketing.scienceconsulting group, inc.
Dr. Augustine Fou
Ad fraud is highly lucrative; there is ample opportunity
“Highly Lucrative, 94% Profit Margins”
The aggregate ad revenue for the sample of 596
sites was an estimated $56.7 million for Q3 of
2013, projecting out to $226.7 million dollars
annually, with average profit margins of 83%,
ranging from 80% to as high as 94%.”
Source: Digital Citizens Alliance Study, Feb 2014
Motive – Most Lucrative More Opportunity
“Fully automated, optimized fraud”
As more digital ads are placed programmatically,
the opportunity for fraud continues to increase.
Bad guys fully automate their digital ad fraud
operations, using programmatic tools to optimize
and maximize profits.
Source: WSJ, March 2014
October 2015 / Page 4marketing.scienceconsulting group, inc.
Dr. Augustine Fou
History of Banner / Display / Impression (CPM) Advertising
Example
Sales Method
Placement
Quantity
of Sites
Fraud Levels
Automation
1995
Yahoo.com
Portals
Direct
Sales
On-site Ad
Placement
10^2
Nascent
n/a
10^9
2000
ESPN.com
Publishers
Direct
Sales
On-site Ad
Placement
10^3
Low
n/a
10^7
2005
Gizmodo.com
Blogs
Network
Sales
Network Ad
Placement
10^6
Medium
Nascent
10^6
2010
Doubleclick
Ad Networks
Network
Sales
Network /
Automated
10^9
High
Automated
10^5Each Site’s
Traffic
2015
AppNexus
Ad Exchanges
RTB/Auction
Programmatic
10^12
Very High
Fully Automated
10^1
October 2015 / Page 5marketing.scienceconsulting group, inc.
Dr. Augustine Fou
Evolution of Impression (CPM) Ad Fraud
2005
Blogs
Need more
visitors
n/a
2010
Ad Networks
Need more traffic to
drive ad impressions
Network / Automated /
Self-serve
2015
Ad Exchanges
Programmatic /
RTB
Motive
Opportunity
10^6 10^9 10^12# of Sites
Types of Fraud n/a
n/a 20% 70%Programmatic
10^6 10^5 10^1Site’s Traffic
More revenues for
more ad impressions
n/a Traffic sourcing and bots
(20% of network traffic)
Bots (60% of
network traffic)
Means
Piracy Sites
10^3
yes
10^7
Need more
visitors
Humans seek
pirated content
Web scrapers /
automated tools
• Malware
• Bot Traffic
• Fake Ad Imp.
• Bot Traffic
• Fake Display Ads
• Fake Video Ads
• All Bot Traffic
• All Fake Ads
• All Fake Clicks
October 2015 / Page 6marketing.scienceconsulting group, inc.
Dr. Augustine Fou
Difference between piracy sites and other ad fraud sites
Piracy Sites Ad Fraud Sites
(CPM fraud)
Click Fraud Sites
(CPC fraud)
Real humans that click (e.g.
click play button)
Traffic Bots: create fake ad
impressions on pageload
Bots: create fake searches
and search clicks
To attract real human users
to plant malware/viruses
Purpose
Pirated movies and music
that humans seek
Content
To carry display ads that can
be sold into ad exchanges
None; or plagiarized content
assembled by algorithm
To carry search ads that
earn revenue share
None; or plagiarized content
assembled by algorithm
56 M /mo
October 2015 / Page 7marketing.scienceconsulting group, inc.
Dr. Augustine Fou
Where piracy sites fit in the digital ad fraud ecosystem
• Malware on humans’ PCs
are used to make botnets
• Real human’s cookies
used for retargeting
Piracy Sites Ad Fraud Sites Click Fraud Sites
Specialty • Bots that cause pages and
ads to load
• Generating display and
video ad impressions
• Advanced bots that can do
“human-like” things like
type search term and click
on CPC ad
• CPM on served ads
• Paid to plant malware
Revenue • CPM on served ads
(display, video)
• CPC on clicks on search ads
(search partner network)
Fraud Types • Malware / Toolbar / Virus
• Sourced Traffic
• Fake Ad Impressions
• Bot Traffic
• Fake Display Ads
• Fake Video Ads
• All Bot Traffic
• All Fake Ads
• All Fake Clicks
October 2015 / Page 8marketing.scienceconsulting group, inc.
Dr. Augustine Fou
Piracy sites provide specialized services to fraud ecosystem
Because piracy sites have real human visitors, they have specialized to provide valuable services
to the fraud ecosystem; and they get paid handsomely for such services.
Malware/Adware (runs on PC) Toolbars / Ad Injection (in browser)
Source: DoubleVerify Case Study
Cookie Cloning (for retargeting) Mouse Movement Recording
Image Source: BenEdelman.org
Source: Forensiq
• smokeybear.com
• rei.com
• travelandleisure.com
• natgeo.com
=
outdoor enthusiast
October 2015 / Page 9marketing.scienceconsulting group, inc.
Dr. Augustine Fou
Dr. Augustine Fou – Recognized Expert on Ad Fraud
2013
2014
2015
SPEAKING ENGAGEMENTS / PANELS
4A’s Webinar on Ad Fraud – October
Digital Ad Fraud Podcast – January
Programmatic Ad Fraud Webinar – March
AdCouncil Webinar on Ad Fraud - April
TelX Marketplace Live – June
ARF Audience Measurement – June
IAB Webinar on Ad Fraud / Botnets - August

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Digital Ad Fraud Ecosystem

  • 1. The Digital Ad Fraud Ecosystem October 2015 Augustine Fou, PhD. acfou [at] mktsci. com 212. 203. 7239
  • 2. October 2015 / Page 1marketing.scienceconsulting group, inc. Dr. Augustine Fou Fraud siphons 1/3 of dollars out of ad ecosystem Advertisers “ad spend” in digital is $56B in 2015 Publishers are left with only 2/3 of the dollars Bad Guys siphon 1/3 of ad spend OUT of the ecosystem • Ad dollars are being siphoned OUT of the ecosystem into the pockets of the bad guys • Advertisers have lower ROI due to fraud (fake impressions/clicks, non-humans/bots) • Publishers have lower revenues (ad dollars stolen by bad guys) 2/3 1/3 Users use ad blocking and need to protect privacy
  • 3. October 2015 / Page 2marketing.scienceconsulting group, inc. Dr. Augustine Fou Bad guys have a whole ecosystem; make money at every point Advertisers “ad spend” in digital is $56B in 2015 Publishers are left with only 2/3 of the dollars “Farmers” Hackers whose job it is to get malware on computers, so botnets can be created. 2/3 1/3 Piracy/Porn Sites Sites that attract real human visitors in order to attempt to plant malware on PCs. Fake Sites Sites with fake content, created solely to carry ads (display, video, search) Fake Visitors/Bots Bots that hit webpages to cause ad impressions, click on ads, collect cookies. Sourced Traffic Unknown users from unknown places that can be purchased for low CPMs Audience Extension Attracting audiences through related content which launders origins. Fake Accounts Fake Facebook, Twitter, LinkedIn, etc. accounts used to gather data/compromise Ad Network Network willing to look the other way because they get a cut of the payout Data Management Fake or falsified data to launder or cover up fraud; also command premiums fraud ecosystem
  • 4. October 2015 / Page 3marketing.scienceconsulting group, inc. Dr. Augustine Fou Ad fraud is highly lucrative; there is ample opportunity “Highly Lucrative, 94% Profit Margins” The aggregate ad revenue for the sample of 596 sites was an estimated $56.7 million for Q3 of 2013, projecting out to $226.7 million dollars annually, with average profit margins of 83%, ranging from 80% to as high as 94%.” Source: Digital Citizens Alliance Study, Feb 2014 Motive – Most Lucrative More Opportunity “Fully automated, optimized fraud” As more digital ads are placed programmatically, the opportunity for fraud continues to increase. Bad guys fully automate their digital ad fraud operations, using programmatic tools to optimize and maximize profits. Source: WSJ, March 2014
  • 5. October 2015 / Page 4marketing.scienceconsulting group, inc. Dr. Augustine Fou History of Banner / Display / Impression (CPM) Advertising Example Sales Method Placement Quantity of Sites Fraud Levels Automation 1995 Yahoo.com Portals Direct Sales On-site Ad Placement 10^2 Nascent n/a 10^9 2000 ESPN.com Publishers Direct Sales On-site Ad Placement 10^3 Low n/a 10^7 2005 Gizmodo.com Blogs Network Sales Network Ad Placement 10^6 Medium Nascent 10^6 2010 Doubleclick Ad Networks Network Sales Network / Automated 10^9 High Automated 10^5Each Site’s Traffic 2015 AppNexus Ad Exchanges RTB/Auction Programmatic 10^12 Very High Fully Automated 10^1
  • 6. October 2015 / Page 5marketing.scienceconsulting group, inc. Dr. Augustine Fou Evolution of Impression (CPM) Ad Fraud 2005 Blogs Need more visitors n/a 2010 Ad Networks Need more traffic to drive ad impressions Network / Automated / Self-serve 2015 Ad Exchanges Programmatic / RTB Motive Opportunity 10^6 10^9 10^12# of Sites Types of Fraud n/a n/a 20% 70%Programmatic 10^6 10^5 10^1Site’s Traffic More revenues for more ad impressions n/a Traffic sourcing and bots (20% of network traffic) Bots (60% of network traffic) Means Piracy Sites 10^3 yes 10^7 Need more visitors Humans seek pirated content Web scrapers / automated tools • Malware • Bot Traffic • Fake Ad Imp. • Bot Traffic • Fake Display Ads • Fake Video Ads • All Bot Traffic • All Fake Ads • All Fake Clicks
  • 7. October 2015 / Page 6marketing.scienceconsulting group, inc. Dr. Augustine Fou Difference between piracy sites and other ad fraud sites Piracy Sites Ad Fraud Sites (CPM fraud) Click Fraud Sites (CPC fraud) Real humans that click (e.g. click play button) Traffic Bots: create fake ad impressions on pageload Bots: create fake searches and search clicks To attract real human users to plant malware/viruses Purpose Pirated movies and music that humans seek Content To carry display ads that can be sold into ad exchanges None; or plagiarized content assembled by algorithm To carry search ads that earn revenue share None; or plagiarized content assembled by algorithm 56 M /mo
  • 8. October 2015 / Page 7marketing.scienceconsulting group, inc. Dr. Augustine Fou Where piracy sites fit in the digital ad fraud ecosystem • Malware on humans’ PCs are used to make botnets • Real human’s cookies used for retargeting Piracy Sites Ad Fraud Sites Click Fraud Sites Specialty • Bots that cause pages and ads to load • Generating display and video ad impressions • Advanced bots that can do “human-like” things like type search term and click on CPC ad • CPM on served ads • Paid to plant malware Revenue • CPM on served ads (display, video) • CPC on clicks on search ads (search partner network) Fraud Types • Malware / Toolbar / Virus • Sourced Traffic • Fake Ad Impressions • Bot Traffic • Fake Display Ads • Fake Video Ads • All Bot Traffic • All Fake Ads • All Fake Clicks
  • 9. October 2015 / Page 8marketing.scienceconsulting group, inc. Dr. Augustine Fou Piracy sites provide specialized services to fraud ecosystem Because piracy sites have real human visitors, they have specialized to provide valuable services to the fraud ecosystem; and they get paid handsomely for such services. Malware/Adware (runs on PC) Toolbars / Ad Injection (in browser) Source: DoubleVerify Case Study Cookie Cloning (for retargeting) Mouse Movement Recording Image Source: BenEdelman.org Source: Forensiq • smokeybear.com • rei.com • travelandleisure.com • natgeo.com = outdoor enthusiast
  • 10. October 2015 / Page 9marketing.scienceconsulting group, inc. Dr. Augustine Fou Dr. Augustine Fou – Recognized Expert on Ad Fraud 2013 2014 2015 SPEAKING ENGAGEMENTS / PANELS 4A’s Webinar on Ad Fraud – October Digital Ad Fraud Podcast – January Programmatic Ad Fraud Webinar – March AdCouncil Webinar on Ad Fraud - April TelX Marketplace Live – June ARF Audience Measurement – June IAB Webinar on Ad Fraud / Botnets - August