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Pinning Down Abuse�on Google Maps

Univ of California, San Diego

Danny Y. Huang, Kirill Levchenko, Alex C. Snoeren

Google

Doug Grundman, Kurt Thomas, �Abhishek Kumar, Elie Bursztein

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Maps SEO is based on physical proximity

2

Traditional�SEO

Ranked by relevance

Example: pharma

Maps�SEO

Ranked by proximity

Example: locksmiths

How many and where?

How to make money?

How to evade detection?

Impact on users?

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7 locksmiths near me

3

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“Locksmith” located at UPS Store

4

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Hard to detect via Street View

5

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Fake locksmiths are an old problem

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Jan 2016

False sense of proximity

Monetize from inferior service

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Overview of abuse on �Google Maps

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Violation of ToS

Caused harm to users

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Overview of abuse on Google Maps

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Listings that Google marked as “abuse”

2014 - 2015

15% reached users

Fake Locations (40%)

locksmiths, plumbers, garage door openers

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Affiliate fraudsters hijack hotel listings

9

Paying for referral traffic

Damages to branding

Reputable �travel agency

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Overview of abuse on Google Maps

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Abusive listings

2014 - 2015

15% reached users

Fake Locations (40%)

locksmiths, plumbers, garage door openers

Affiliate Fraud (13%)

hotels, restaurants

Misc (47%)

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Abuse varies across countries

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0%

20%

40%

60%

80%

100%

% of abusive listings in each country

USA

India

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Abuse varies across countries

12

locksmiths

plumbers, etc

0%

20%

40%

60%

80%

100%

% of abusive listings in each country

USA

India

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Abuse varies across countries

13

hotels

% of abusive listings in each country

locksmiths

plumbers, etc

0%

20%

40%

60%

100%

USA

India

80%

% of abusive listings in each country

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How did scammers evade Google’s detection?

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Creating a free listing on Google Maps

Google My Business

Reviewer

Google Map Maker

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Creating a free listing on Google Maps

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Verification via mail

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80% abusive listings verified through mail

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Creating listings with fake locations

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Residential

Commercial

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Verifying listings using the same address

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123 Main St

123 Main St Suite 456�123 Main St #456�#456 123 Main St

l23 Main St

Verify multiple listings��25% of abusive listings �used this trick

Impose a cutoff?

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Abusive listings verified at the same address

20

>1,000

101 - 1,000

11 - 100

2 - 10

1

# Listings at same address

0%

20%

40%

60%

80%

100%

Probability of abusive listings

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Abusive listings verified at the same address

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>1,000

101 - 1,000

11 - 100

2 - 10

1

# Listings at same address

0%

20%

40%

60%

80%

100%

Probability of abusive listings

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Abusive listings can be reached at VoIP numbers

Carrier	Abusive	Non-abusive
Bandwidth
Ring Central
Level 3
Misc VoIP Carriers
Other Carriers

Non-VoIP Carriers

VoIP Carriers

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Abusive listings can be reached at VoIP numbers

Carrier	Abusive	Non-abusive
Bandwidth	33%	3%
Ring Central	13%	1%
Level 3	10%	4%
Misc VoIP Carriers	13%	3%
Other Carriers	31%	89%

Non-VoIP Carriers

VoIP Carriers

Example: Of the abusive listings with phone numbers, 33% of them used the carrier Bandwidth.

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Impact on end users?

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Quantifying impact on users

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# of abusive search results

# of search results

Locksmiths

11%

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Search results that are abusive

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Locksmiths

11%

Plumbers, etc

0.4%

New York, NY

16%

West Harrison, NJ

84%

Restaurants

1%

Hotels

1%

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Pie chart: abusive results that are locksmiths

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Locksmiths

11%

Plumbers, etc

0.4%

Restaurants

1%

Hotels

1%

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Pie chart: abusive results that are plumbers etc

28

Locksmiths

11%

Plumbers, etc

0.4%

Restaurants

1%

Hotels

1%

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Pie chart: abusive results that are hotels

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Locksmiths

11%

Plumbers, etc

0.4%

Restaurants

1%

Hotels

1%

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Pie chart: abusive results that are restaurants

30

Locksmiths

11%

Plumbers, etc

0.4%

Restaurants

1%

Hotels

1%

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Overall search results that are abusive

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Locksmiths

11%

Plumbers, etc

0.4%

Restaurants

1%

Hotels

1%

0.5%

of search results in US were abusive

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Summary

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SEO based on physical proximity

Fake locations vs affiliate fraud

Hard to verify addresses at scale

Improved defenses by Google;�abusive listings down by 70% from peak

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Thank you!

More info: http://sysnet.ucsd.edu/~dhuang/

Univ of California, San Diego

Danny Y. Huang, Kirill Levchenko, Alex C. Snoeren

Google

Doug Grundman, Kurt Thomas, �Abhishek Kumar, Elie Bursztein