1. Characterizing Pixel Tracking through the Lens of Disposable Email Services
Authors: Hang Hu, Peng Peng, Gang Wang
Department of Computer Science, Virginia Tech
{hanghu, pengp17,
COMPSCI 726: Network Defence and Countermeasures
Presented by David Zhai

2. Introduction and Background

3. Motivation
Understand the disposable services (DES) and the risks
- Collect data from seven popular DES for three months
Use DES to collect large-scale dataset for measuring Tracking
- Tracking pixel
Picture resource:

4. Disposable Email Services (DES)
Provide temporary addresses
No sign up or password required
User-specified address (UA) or Randomly-assigned address (RA)
Shared by multiple users
Automatically delete after a short period (e.g. one hour)

5. One Example of DES
Picture resource:

6. Solution and Analysis

7. DES Data Collection 70K Inboxes 210K Domains 2.3M Emails
10K popular usernames:
“info”
“John”
“admin”
“mail”
“David” …
7 popular disposable services
70K Inboxes
210K Domains
2.3M s
3 months

8. DES Analysis Categories of Disposable Emails
Account Registration
Password Reset
Authentication
Spam
Categories of Senders
Top 10 categories of the sender domains for Account Management and Spam s
Usage
Register accounts (Gaming, social network)
Obtain free goods (Demos, documents, free Wi-Fi)

9. DES Risks
Disposable services do not remove s as quickly as promised
Personally Identifiable Information (PII) in s
Credit card number
Social security number (SSN)
Employer identification number
Online accounts registered by DES can be hijacked through a password reset

10. 1x1 tracking pixel, usually hidden
Pixel Tracking
A common method – Small image at end of , usually transparent 1x1 pixel
Tracking information
When
Where
Who
What device
Why tracking
For business, e.g. advertisement
Phishers
1x1 tracking pixel, usually hidden

11. Email Tracking Detection and Analysis
Extract HTML image tags and corresponding URLs of a given
Third-party tracking is highly prevalent
Marketing services have the highest ratio of tracking.

12. Contribution and Criticism

13. Contribution First measurement study on disposable email services
Introduced DES and risks
Collected big dataset and analysed messages content
Analysed Tracking activities
Characterizing tracking pixels
Insights into the prevalence of tracking
Valuable for developing anti-tracking tools for systems

14. Criticism DES understanding – Could be extended
Measurement – Incomplete scope (Based on User-specified Addresses)
About the risk: Online accounts registered by DES can be hijacked through a password reset? – Not exactly
DES is not representative – Not real user
Analyses mainly based on Spam s – Not accurate result

15. Thank you!