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Nowhere to Hide: Detecting Obfuscated Fingerprinting Scripts

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arxiv 2206.13599 v1 pith:RDNU7XRG submitted 2022-06-27 cs.CR

classification cs.CR
keywords fingerprintinganalysisobfuscationabledetectdynamicstaticbrowser
verification ladder T0 review T1 audit T2 compute T3 formal
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As the web moves away from stateful tracking, browser fingerprinting is becoming more prevalent. Unfortunately, existing approaches to detect browser fingerprinting do not take into account potential evasion tactics such as code obfuscation. To address this gap, we investigate the robustness of a state-of-the-art fingerprinting detection approach against various off-the-shelf obfuscation tools. Overall, we find that the combination of static and dynamic analysis is robust against different types of obfuscation. While some obfuscators are able to induce false negatives in static analysis, dynamic analysis is still able detect these cases. Since obfuscation does not induce significant false positives, the combination of static and dynamic analysis is still able to accurately detect obfuscated fingerprinting scripts.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Byte by Byte: Unmasking Browser Fingerprinting at the Function Level Using V8 Bytecode Transformers

    cs.CR 2025-09 conditional novelty 6.0 of 10

    ByteDefender uses a Transformer trained on V8 bytecode to label individual JavaScript functions as fingerprinting or not, claiming function-level detection with 4% page-load overhead.

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