Brave Proposes a Machine Learning Approach for Ad Blocking
AdGraph alleviates the need for manual filter list curation by using machine learning to automatically identify patterns in the page load process to block ads and trackers. AdGraph automatically and effectively blocks ads and trackers with 97.7% accuracy. AdGraph even has better recall than filter lists, as it blocks 16% more ads and trackers with 65% accuracy. The analysis also shows that AdGraph is fairly robust against adversarial obfuscation by publishers and advertisers that bypass filter lists.
Brave’s Chief Scientist, Dr. Ben Livshits, worked with Peter Snyder, a privacy researcher at Brave, and researchers from the University of Iowa (Umar Iqbal and Zubair Shafiq) and the University of California Riverside (Shitong Zhu and Zhiyun Qian) on this project. The full paper can be downloaded from ArXiV.org here. The team is looking at deploying these techniques within Brave over time.
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Because crowdsourced filter lists used by state-of-the-art ad blockers can be easily evaded using simple obfuscation techniques, AdGraph’s resistance to those obfuscation attempts by publishers and advertisers represents an important technical advancement in the rapidly escalating ad blocking arms race.
The new Brave browser blocks the ads and trackers that slow you down, chew up your bandwidth, and invade your privacy. Brave even lets you contribute to your favorite creators automatically.
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