A FIRST LOOK AT AD-BLOCK DETECTION – A NEW ARMS RACE ON THE WEB

MPhil Thesis Defence


Title: "A FIRST LOOK AT AD-BLOCK DETECTION – A NEW ARMS RACE ON THE WEB"

By

Mr. Muhammad Haris MUGHEES


Abstract

The rise of ad-blockers is viewed as an economic threat by online 
publishers, especially those who primarily rely on advertising to support 
their services. To address this threat, publishers have started 
retaliating by employing ad-block detectors, which scout for ad-blocker 
users and react to them by restricting their content access and pushing 
them to whitelist the website or disabling ad-blockers altogether. The 
clash between ad-blockers and ad-block detectors has resulted in a new 
arms race on the web.

In this thesis, we present the first systematic measurement and analysis 
of ad-block detection on the web. We have designed and implemented a 
machine learning based technique to automatically detect ad-block 
detection, and use it to study the deployment of ad-block detectors on 
Alexa top- 100K websites. The approach is promising with precision of 
94.8% and recall of 93.1%. We characterize the spectrum of different 
strategies used by websites for ad-block detection. We find that a vast 
majority of publishers on the web use fairly simple passive approaches for 
ad-block detection. However, we also note that a few websites use 
third-party services, e.g. PageFair, for ad-block detection and response. 
The third-party services use active deception and other sophisticated 
tactics to detect ad-blockers. We also find that the third-party services 
can successfully circumvent ad-blockers and display ads on publisher 
websites. Finally, we design and implement a proof-of- concept stealthy 
ad-blocker that can circumvent state-of-the-art ad-block detectors.


Date:			Thursday, 23 June 2016

Time:			4:00pm - 6:00pm

Venue:			Room 2611
 			Lifts 31/32

Committee Members:	Dr. Pan Hui (Supervisor)
 			Dr. Raymond Wong (Chairperson)
 			Prof. Gary Chan


**** ALL are Welcome ****