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Abstract
As third-party cookie blocking is becoming the norm in browsers, advertisers
and trackers have started to use first-party cookies for tracking. We conduct a
differential measurement study on 10K websites with third-party cookies allowed
and blocked. This study reveals that first-party cookies are used to store and
exfiltrate identifiers to known trackers even when third-party cookies are
blocked.
As opposed to third-party cookie blocking, outright first-party cookie
blocking is not practical because it would result in major functionality
breakage. We propose CookieGraph, a machine learning-based approach that can
accurately and robustly detect first-party tracking cookies. CookieGraph
detects first-party tracking cookies with 90.20% accuracy, outperforming the
state-of-the-art CookieBlock approach by 17.75%. We show that CookieGraph is
fully robust against cookie name manipulation while CookieBlock's acuracy drops
by 15.68%. While blocking all first-party cookies results in major breakage on
32% of the sites with SSO logins, and CookieBlock reduces it to 10%, we show
that CookieGraph does not cause any major breakage on these sites.
Our deployment of CookieGraph shows that first-party tracking cookies are
used on 93.43% of the 10K websites. We also find that first-party tracking
cookies are set by fingerprinting scripts. The most prevalent first-party
tracking cookies are set by major advertising entities such as Google,
Facebook, and TikTok.