Several top websites use device fingerprinting to secretly track users

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Several top websites use device fingerprinting to secretly track users : http://phys.org/news/2013-10-websites-device-fingerprinting-secretly-track.html

(Phys.org) —A new study by KU Leuven-iMinds researchers has uncovered that 145 of the Internet's 10,000 top websites track users without their knowledge or consent. The websites use hidden scripts to extract a device fingerprint from users' browsers. Device fingerprinting circumvents legal restrictions imposed on the use of cookies and ignores the Do Not Track HTTP header. The findings suggest that secret tracking is more widespread than previously thought.

Device fingerprinting, also known as browser fingerprinting, is the practice of collecting properties of PCs, smartphones and tablets to identify and track users. These properties include the screen size, the versions of installed software and plugins, and the list of installed fonts. A 2010 study by the Electronic Frontier Foundation (EFF) showed that, for the vast majority of browsers, the combination of these properties is unique, and thus functions as a 'fingerprint' that can be used to track users without relying on cookies. Device fingerprinting targets either Flash, the ubiquitous browser plugin for playing animations, videos and sound files, or JavaScript, a common programming language for web applications.
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To detect websites using device fingerprinting technologies, the researchers developed a tool called FPDetective. The tool crawls and analyses websites for suspicious scripts.
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FPDetective - the Paper : http://homes.esat.kuleuven.be/~gacar/fpdetective/

The paper "FPDetective: Dusting the Web for Fingerprinters" (PDF) describes the first comprehensive effort to measure the prevalence of device fingerprinting on the Internet. It will be presented at the 20th ACM Conference on Computer and Communications Security that takes place in Berlin in November.
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FPDetective is designed as a flexible, general purpose framework that can be used to conduct large scale web privacy studies. The framework is developed using Python, C++(browser modifications), JavaScript and MySQL programming/scripting languages.
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