On Web User Tracking: How Third-Party Http Requests Track Users' Browsing Patterns for Personalised Advertising

TL;DR

This paper examines how third-party HTTP requests on the web track user browsing patterns, creating detailed profiles that influence personalized advertising, and analyzes the impact of user behavior changes on ad targeting.

Contribution

It provides an analysis of how advertising networks construct user footprints through third-party requests and how these profiles adapt to behavioral changes.

Findings

Third-party requests effectively track user browsing patterns.

User profiles influence personalized advertising.

Behavioral changes impact ad targeting accuracy.

Abstract

On today's Web, users trade access to their private data for content and services. Advertising sustains the business model of many websites and applications. Efficient and successful advertising relies on predicting users' actions and tastes to suggest a range of products to buy. It follows that, while surfing the Web users leave traces regarding their identity in the form of activity patterns and unstructured data. We analyse how advertising networks build user footprints and how the suggested advertising reacts to changes in the user behaviour.