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On the modern web, trackers and advertisers frequently construct and monetizeusers' detailed behavioral profiles without consent. Despite various studies onweb tracking mechanisms and advertisements, there has been no rigorous studyfocusing on websites targeted at children. To address this gap, we present ameasurement of tracking and (targeted) advertising on websites directed atchildren. Motivated by lacking a comprehensive list of child-directed (i.e.,targeted at children) websites, we first build a multilingual classifier basedon web page titles and descriptions. Applying this classifier to over twomillion pages, we compile a list of two thousand child-directed websites.Crawling these sites from five vantage points, we measure the prevalence oftrackers, fingerprinting scripts, and advertisements. Our crawler detects adsdisplayed on child-directed websites and determines if ad targeting is enabledby scraping ad disclosure pages whenever available. Our results show thataround 90% of child-directed websites embed one or more trackers, and about 27%contain targeted advertisements--a practice that should require verifiableparental consent. Next, we identify improper ads on child-directed websites bydeveloping an ML pipeline that processes both images and text extracted fromads. The pipeline allows us to run semantic similarity queries for arbitrarysearch terms, revealing ads that promote services related to dating, weightloss, and mental health; as well as ads for sex toys and flirting chatservices. Some of these ads feature repulsive and sexually explicit imagery. Insummary, our findings indicate a trend of non-compliance with privacyregulations and troubling ad safety practices among many advertisers andchild-directed websites. To protect children and create a safer onlineenvironment, regulators and stakeholders must adopt and enforce more stringentmeasures.

Targeted and Troublesome: Tracking and Advertising on Children's Websites