  On the modern web, trackers and advertisers frequently construct and monetize
users' detailed behavioral profiles without consent. Despite various studies on
web tracking mechanisms and advertisements, there has been no rigorous study
focusing on websites targeted at children. To address this gap, we present a
measurement of tracking and (targeted) advertising on websites directed at
children. Motivated by lacking a comprehensive list of child-directed (i.e.,
targeted at children) websites, we first build a multilingual classifier based
on web page titles and descriptions. Applying this classifier to over two
million pages, we compile a list of two thousand child-directed websites.
Crawling these sites from five vantage points, we measure the prevalence of
trackers, fingerprinting scripts, and advertisements. Our crawler detects ads
displayed on child-directed websites and determines if ad targeting is enabled
by scraping ad disclosure pages whenever available. Our results show that
around 90% of child-directed websites embed one or more trackers, and about 27%
contain targeted advertisements--a practice that should require verifiable
parental consent. Next, we identify improper ads on child-directed websites by
developing an ML pipeline that processes both images and text extracted from
ads. The pipeline allows us to run semantic similarity queries for arbitrary
search terms, revealing ads that promote services related to dating, weight
loss, and mental health; as well as ads for sex toys and flirting chat
services. Some of these ads feature repulsive and sexually explicit imagery. In
summary, our findings indicate a trend of non-compliance with privacy
regulations and troubling ad safety practices among many advertisers and
child-directed websites. To protect children and create a safer online
environment, regulators and stakeholders must adopt and enforce more stringent
measures.
