We have written before on Brave’s performance, energy and bandwidth benefits for the user. Brave Shields is our primary mechanism for protecting user privacy, but many users know by now that ad and tracker blocking (or just ad blocking for short) makes the web faster and generally better for them. So far Brave’s estimates of the users’ time saved have been very conservative and somewhat naive: we take the total number of ads and trackers blocked, and multiply that by 50 milliseconds.
Brave Shields, which protect users’ privacy from trackers and ads, are one of the cornerstone components of the browser involved in handling every single web request made for loading a website.
We are constantly looking to improve and automate the accuracy and speed of ad blocking built into Brave, and our previous post outlined a machine learning approach to ad blocking.
This week, Brave unveiled new research that is under submission to an upcoming conference regarding how to improve and automate ad blocking with AdGraph, a graph-based machine learning approach for detecting ads and trackers on a given web page.
