National Cyber Warfare Foundation (NCWF)

NDSS 2025 – Duumviri: Detecting Trackers And Mixed Trackers With A Breakage Detector


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2025-11-07 00:21:35
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SESSION

Session 2B: Web Security


Authors, Creators & Presenters: He Shuang (University of Toronto), Lianying Zhao (Carleton University and University of Toronto), David Lie (University of Toronto)


PAPER

Duumviri: Detecting Trackers and Mixed Trackers with a Breakage Detector

https://www.ndss-symposium.org/wp-con…

Web tracking harms user privacy. As a result, the use of tracker detection and blocking tools is a common practice among Internet users. However, no suchtool can be perfect, and thus there is a trade-off between avoiding breakage (caused by unintentionally blocking some required functionality) and neglecting toblock some trackers. State-of-the-art tools usually rely on user reports and developer effort to detect breakages, which can be broadly categorized into two causes: 1) misidentifying non-trackers as trackers, and 2) blocking mixed trackers which blend tracking with functional components.

We propose Incorporating a machine learning-based break- age detector into the tracker detection pipeline to automatically avoid misidentification of

functional resources. For both tracker detection and breakage detection, we propose using differential features that can more clearly elucidate the differences caused by blocking a request. We designed and implemented a prototype of our proposed approach, Duumviri, for non-mixed trackers. We then adopt it to automatically identify mixed trackers, drawing differential features at partial-request granularity.

In the case of non-mixed trackers, evaluating Duumviri on 15K pages shows its ability to replicate the labels of human-generated filter lists, EasyPrivacy, with an accuracy of 97.44%. Through a manual analysis, we find that Duumviri can identify previously unreported trackers and its breakage detector can identify overly strict EasyPrivacy rules that cause breakage. In the case of mixed trackers, Duumviri is the first automated mixed tracker detector, and achieves a lower bound accuracy of 74.19%. Duumviri has enabled us to detect and confirm 22 previously unreported unique trackers and 26 unique mixed trackers.


Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the organization’s’ YouTube channel.


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The post NDSS 2025 – Duumviri: Detecting Trackers And Mixed Trackers With A Breakage Detector appeared first on Security Boulevard.



Marc Handelman

Source: Security Boulevard
Source Link: https://securityboulevard.com/2025/11/ndss-2025-duumviri-detecting-trackers-and-mixed-trackers-with-a-breakage-detector/


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