We have now entered the era of trillion parameter machine learning models trained on
billion-sized datasets scraped from the internet. The rise of these gargantuan datasets has …

Whereas much of the success of the current generation of neural language models has
been driven by increasingly large training corpora, relatively little research has been …

General-purpose artificial intelligence (AI) systems are built on massive swathes of public
web data, assembled into corpora such as C4, RefinedWeb, and Dolma. To our knowledge …

Web tracking has evolved to become a norm on the Internet. As a matter of fact, the web
tracking market has grown to raise billions of dollars. Privacy cautious web practitioners and …

Over the past years, advertisement companies have used various tracking methods to
persistently track users across the web. Such tracking methods usually include first and third …

In this work, we tackle the problem of classifying websites domain names to a category, eg,
mapping bbc. com to the” News and Media” class. Domain name classification is …

In recent years, governments worldwide have moved their services online to better serve
their citizens. Benefits aside, this choice increases the danger of tracking via such sites. This …

We present a Federated Learning (FL) based solution for building a distributed classifier
capable of detecting URLs containing GDPR-sensitive content related to categories such as …

Despite researchers have noticed that Looking Glass (LG) vantage points (VPs) are
valuable for Internet measurement researches, they can only exploit VPs from well-known …

Free and open-source media centers are experiencing a boom in popularity for the
convenience they offer users seeking to remotely consume digital content. Kodi is today's …