Abstract
Browser fingerprinting is a technique to identify a browser based on device features collected by a web server. Previous studies have been proposed the use of various features; however, to the best of our knowledge, the correlation between features combinations and identification accuracy has never been considered. Thus, in this study, we calculated the identification accuracy of different combinations of features using 9,457 samples of fingerprints collected on our website to collect fingerprints. Consequently, compared to Panopticlick [1], we realized 1.006%, 3.894%, 7.456%, and 3.840% identification accuracy improvement on the Windows, Mac, iOS, and Android operating systems, respectively.
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References
Eckersley, P.: How unique is your web browser? In: Proceedings of the 10th International Conference on Privacy Enhancing Technologies (PETS 2010) (2010)
Laperdrix, P., Rudametkin, W., Baudry, B.: Beauty and the beast: diverting modern web browsers to build unique browser fingerprints. In: Proceedings of 37th IEEE Symposium on Security and Privacy (S&P 2016) (2016)
Mowery, K., Shacham, H.: Pixel perfect: fingerprinting canvas in HTML5. In: Proceedings of Web 2.0 Security and Privacy (W2SP) (2012)
Englehardt, S., Narayanan, A.: Online tracking: a 1-million-site measurement and analysis. In: Proceedings of ACM Conference on Computer and Communications Security (CCS 2016) (2016)
Saito, T., Yasud, K., Tanabe, K., Takahashi, K.: Web browser tampering: inspecting CPU features from side-channel information. In: Broad-Band Wireless Computing, Communication and Applications (2017)
Iso, Y., Kiryu, N., Tsukamoto, K., Takasu, K., Yamada, T., Takei, N., Saito, T.: An implementation of browser fingerprinting website and analysis of its collected data. In: Computer Security Symposium 2014 (CSS 2014) (2014)
Takasu, K., Saito, T., Yamada, T., Ishikawa, T.: A survey of hardware features in modern browsers. In: Proceedings of Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS 2015) (2015)
Fingerprint collection site. https://www.saitolab.org/fingerprint/
Alexa top sites. https://www.alexa.com/topsites/
Tor Bug Tracker & Wiki. https://trac.torproject.org/projects/tor/ticket/6119
Passive OS Fingerprinting: Details and Techniques. http://www.ouah.org/incosfingerp.htm
MediaStreamTrack. https://developer.mozilla.org/en-US/docs/Web/API/ediaStreamTrack
Google Maps Geolocation API. https://developers.google.com/maps/documentation/geolocation/intro
WEBGL\({\_}\)debug\({\_}\)render\({\_}\)info. https://developer.mozilla.org/en-US/docs/Web/API/WEBGL_debug_renderer_info
Tor Project: Anonymity Onlineâexit-addresses. https://check.torproject.org/exit-addresses
Acknowledgement
This work was supported by JSPS KAKENHI Grant Number 18K11305. We are deeply grateful to Takayuki Ishikawa, Rio Hosoi, Kazushi Takahashi, and Koki Yasuda.
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Tanabe, K., Hosoya, R., Saito, T. (2019). Combining Features in Browser Fingerprinting. In: Barolli, L., Leu, FY., Enokido, T., Chen, HC. (eds) Advances on Broadband and Wireless Computing, Communication and Applications. BWCCA 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-030-02613-4_60
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DOI: https://doi.org/10.1007/978-3-030-02613-4_60
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