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Fraud Detection is Easily Fooled

What's worse than a lot of ad fraud? Detecting it wrong, and thinking there isn't any (fraud).

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Fraud Detection is
Easily Fooled
August 2017
Augustine Fou, PhD.
acfou [at] mktsci.com
212. 203 .7239
August 2017 / Page 1marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Bad guys’ tool to trick detection
Source: Ratko Vidakovic
August 2017 / Page 2marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Fraudsters successfully sell ads… how?
100% viewability
(but, it’s fake)
AD
Stack ads all
above the fold to
trick detection
0% NHT
(but, it’s fake)
Buy traffic that is
guaranteed to
pass fraud filters
clean placement
(but, it’s fake)
Pass fake source
to trick reports of
placement details
http://www.olay.co
m/skin-care-
products/OlayPro-
X?utm_source=elle
&utm_medium=dis
play
+ +
“by tricking measurement and reporting”
August 2017 / Page 3marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Current detection cannot catch it
In-Ad
(billions of ads)
• Limitations –
tag is in foreign
iframe, cannot look
outside itself
ad tag / pixel
(in-ad measurement)
In-Network
(trillions of bids)
On-Site
(millions of pageviews)
javascript embed
(on-site measurement)
• Limitations –
most detailed
analysis of visitors,
bots still get by
• Limitations –
relies on blacklists
or probabilistic
algorithms, least info
ad
served
bot
human
fraud site
good site
August 2017 / Page 4marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Just because you can’t measure it
100%
fraud
> 50% fraud
… doesn’t mean it’s not there.
August 2017 / Page 5marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Mobile is fraught with fraud, NOT 2%
1 2
66% avg fraud
18% avg fraud
1. 9% of the apps (blue dots) caused 52% of impressions; 66% fraudulent
2. 91% of apps caused the 48% of impressions; 18% fraudulent
• 1 billion mobile display impressions
• Nearly 1,000 apps cross referenced with SDK

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Fraud Detection is Easily Fooled

  • 1. Fraud Detection is Easily Fooled August 2017 Augustine Fou, PhD. acfou [at] mktsci.com 212. 203 .7239
  • 2. August 2017 / Page 1marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bad guys’ tool to trick detection Source: Ratko Vidakovic
  • 3. August 2017 / Page 2marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Fraudsters successfully sell ads… how? 100% viewability (but, it’s fake) AD Stack ads all above the fold to trick detection 0% NHT (but, it’s fake) Buy traffic that is guaranteed to pass fraud filters clean placement (but, it’s fake) Pass fake source to trick reports of placement details http://www.olay.co m/skin-care- products/OlayPro- X?utm_source=elle &utm_medium=dis play + + “by tricking measurement and reporting”
  • 4. August 2017 / Page 3marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Current detection cannot catch it In-Ad (billions of ads) • Limitations – tag is in foreign iframe, cannot look outside itself ad tag / pixel (in-ad measurement) In-Network (trillions of bids) On-Site (millions of pageviews) javascript embed (on-site measurement) • Limitations – most detailed analysis of visitors, bots still get by • Limitations – relies on blacklists or probabilistic algorithms, least info ad served bot human fraud site good site
  • 5. August 2017 / Page 4marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Just because you can’t measure it 100% fraud > 50% fraud … doesn’t mean it’s not there.
  • 6. August 2017 / Page 5marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Mobile is fraught with fraud, NOT 2% 1 2 66% avg fraud 18% avg fraud 1. 9% of the apps (blue dots) caused 52% of impressions; 66% fraudulent 2. 91% of apps caused the 48% of impressions; 18% fraudulent • 1 billion mobile display impressions • Nearly 1,000 apps cross referenced with SDK
  • 7. August 2017 / Page 6marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Methbot avoided detection for years Source: Dec 2016 WhiteOps Discloses Methbot Research “Methbot, steals $2 billion annualized; and it avoided detection for years.” 1. Targeted video ad inventory $13 average CPM, 10X higher than display ads 2. Disguised as good publishers Pretending to be good publishers to cover tracks 3. Simulated human actions Actively faked clicks, mouse movements, page scrolling 4. Obfuscated data center origins Data center bots pretended to be from residential IP addresses
  • 8. August 2017 / Page 7marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Plainly incorrect measurements Incorrect IVT Measurement Sources 1 and 2 measured on-page Source 3 in foreign iframe 1x1 pixel incorrectly reported as 100% viewable Incorrect Viewability
  • 9. August 2017 / Page 8marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Tag placement yields opposite results Tag (in foreign iframe) Tag (on page) window sizes detected as 0x0 or 0x8 pixels correct window sizes for ads detected 0% humans 60% bots 60% humans 3% bots “fraud measurements could be entirely wrong, depending on where the tag is placed and where the measurement is done.”
  • 10. August 2017 / Page 9marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 3 bad apps eat 3/4ths of budget flashlight app 75% of the dark red keyboard app alarm clock app
  • 11. August 2017 / Page 10marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Fake inventory sold on exchanges publisherA.com … but, PublisherA does NOT sell ads on open exchanges! “Dark Revenue” is ad revenue diverted away from publishers, so they don’t even see it’s missing. • Large pubs – “dark” is 1-2X ad revenue • Medium pubs - “dark” is 5-10X ad revenue • Small pubs - “dark” is 20-100X ad revenue
  • 12. August 2017 / Page 11marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Facebook viewability low? No problem “Agencies continue to accuse Facebook. Assuming Facebook viewability is actually as low as 20%... No problem, because it’s still 5X more effective and sends 10-99X more humans than other programmatic display sources!”
  • 13. August 2017 / Page 12marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bad media buying goes unnoticed Most of budget wasted between 12a – 4a Media turned off between 2a-5a
  • 14. August 2017 / Page 13marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Dr. Augustine Fou – Independent Ad Fraud Researcher 2013 2014 Follow me on LinkedIn (click) and on Twitter @acfou (click) Further reading: http://www.slideshare.net/augustinefou/presentations https://www.linkedin.com/today/author/augustinefou 2016 2015