What Fraudulent Traffic Looks Like Research by Augustine Fou


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There are normal patterns to humans visiting websites -- for example, they search for something first and then go to the site, they sleep at night and visit websites during the day, etc. When there are unusual and large changes to site traffic, something is suspicious -- and it is likely done by bots (i.e. non human traffic - NHT).

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What Fraudulent Traffic Looks Like Research by Augustine Fou

  1. 1. Augustine Fou- 1 - What Fraudulent Traffic Looks Like Dr. Augustine Fou http://linkd.in/augustinefou acfou @mktsci .com July 2014
  2. 2. Augustine Fou- 2 - Use Bots to Load the Pages Source: Wired Source: Google Digital Attack Map
  3. 3. Augustine Fou- 3 - Traffic Firehose On/Off Legit human traffic does not change rapidly; but bot traffic (firehose) can be rapidly turned off and directed to other sites. Source: Alexa Source: spider.io
  4. 4. Augustine Fou- 4 - Large Changes in Traffic Source: Quantcast Shows exactly when bot traffic was turned off (drop to zero) and then was turned back on (traffic out of nowhere)
  5. 5. Augustine Fou- 5 - Fake Video Views Source: Socialbakers Channel Stats Tool • Daily traffic is identical • Botnet views turned off, then back on
  6. 6. Augustine Fou- 6 - Video Ad Fraud (Dec 2013) Leaked Document Shows How Big Brands' Video Ad Budgets Get Spent On Asian Porn Sites – By: Jim Edwards Read more: http://www.businessinsider.com/tele metry-document-ad-budgets-asian-porn- 2013-12#ixzz2sawbKAL4 • Video views from 5 different sites, acoss multiple days is exactly the same (this is not normal)
  7. 7. Augustine Fou- 7 - Humans Sleep At Night Hourly traffic charts show lower traffic at night (as expected because human visitors sleep at night) Unusual traffic patterns with no normal night time trends visible, possibly due to bot activity
  8. 8. Augustine Fou- 8 - Weekday vs Weekend Normal traffic pattern for weekday vs weekend (weekends are lower) Something is strange here because daily traffic should not be exactly the same as every other day (i.e. no normal weekday vs weekend cyclces)
  9. 9. Augustine Fou- 9 - Search Volume Doesn’t Support Source: Quantcast search interest pattern
  10. 10. Augustine Fou- 10 - Dr. Augustine Fou – Digital Consigliere “I research ad fraud so I can advise clients on how to detect and mitigate it. This has the most direct mpact on the ROI of their digital marketing programs.” FORMER CHIEF DIGITAL OFFICER, HCG (OMNICOM) MCKINSEY CONSULTANT CLIENT SIDE / AGENCY SIDE EXPERIENCE PROFESSOR AND COLUMNIST ENTREPRENEUR / SMALL BUSINESS OWNER PHD MATERIALS SCIENCE (MIT '95) AT AGE 23 @acfou ClickZ Articles: http://bit.ly/augustine-fou-clickz Slideshares: http://bit.ly/augustine-fou-slideshares LinkedIn: https://www.linkedin.com/today/author/84444-augustinefou
  11. 11. Augustine Fou- 11 - Related Articles Augustine Fou- 11 - http://www.slideshare.net/augustinefou/how-click-fraud-search-ad-fraud- works-analysis-by-augustine-fou http://www.slideshare.net/augustinefou/proof-positive-click-fraud- impacting-retailers-by-augustine-fou http://www.slideshare.net/augustinefou/proof-positive-click-fraud-sites- investigation-by-augustine-fou http://www.slideshare.net/augustinefou/ad-fraud-estimates-by-augustine-fou- technical-forensics-32293935 http://www.slideshare.net/augustinefou/fake-traffic-site-examples-2014- augustine-fou