arXiv:1503.01408cs.CR
Hardware Fingerprinting Using HTML5
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Abstract
Device fingerprinting over the web has received much attention both by the research community and the commercial market a like. Almost all the fingerprinting features proposed to date depend on software run on the device. All of these features can be changed by the user, thereby thwarting the device's fingerprint. In this position paper we argue that the recent emergence of the HTML5 standard gives rise to a new class of fingerprinting features that are based on the \emph{hardware} of the device. Such features are much harder to mask or change thus provide a higher degree of confidence in the fingerprint. We propose several possible fingerprint methods that allow a HTML5 web application to identify a device's hardware. We also present an initial experiment to fingerprint a device's GPU.
Panopticlick doesn't use everything available. WebGL alone adds an additional 5.11 bits of entropy[1]. Other things such as your local network address from WebRTC, core count, etc. all can add a lot more entropy for fingerprinting. [1]: http://arxiv.org/pdf/1503.01408.pdf
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