# Ad-Blocking and Counter Blocking: A Slice of the Arms Race

arXiv: https://arxiv.org/abs/1605.05077 · HTML: https://mlsanity.com/paper/1605.05077/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 May 2016.

## Built on by (most cited first, 5 of 5)

- [Testing Human Ability To Detect Deepfake Images of Human Faces](https://mlsanity.com/paper/2212.05056/) (2022)
- [Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioning](https://mlsanity.com/paper/2210.07770/) (2022)
- [HARPO: Learning to Subvert Online Behavioral Advertising](https://mlsanity.com/paper/2111.05792/) (2021)
- [Collaborative Domain Blocking: Using federated NLP To Detect Malicious Domains](https://mlsanity.com/paper/2210.04088/) (2022)
- [Agentic AI: User Empowerment or Foreclosure?](https://mlsanity.com/paper/2608.06510/) (2026)

## Abstract (arXiv)

Adblocking tools like Adblock Plus continue to rise in popularity, potentially threatening the dynamics of advertising revenue streams. In response, a number of publishers have ramped up efforts to develop and deploy mechanisms for detecting and/or counter-blocking adblockers (which we refer to as anti-adblockers), effectively escalating the online advertising arms race. In this paper, we develop a scalable approach for identifying third-party services shared across multiple web-sites and use it to provide a first characterization of anti-adblocking across the Alexa Top-5K websites. We map websites that perform anti-adblocking as well as the entities that provide anti-adblocking scripts. We study the modus operandi of these scripts and their impact on popular adblockers. We find that at least 6.7% of websites in the Alexa Top-5K use anti-adblocking scripts, acquired from 12 distinct entities -- some of which have a direct interest in nourishing the online advertising industry.