FPRandom: Randomizing Core Browser Objects to Break Advanced Device Fingerprinting Techniques
FPRandom: Randomizing Core Browser Objects to Break Advanced Device Fingerprinting Techniques
复制标题
FPRandom：随机化核心浏览器对象以破坏先进的设备指纹识别技术
DOI：
10.1007/978-3-319-62105-0_7
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Vikas Mishra
中科院分区：
文献类型：
--
作者：
Pierre Laperdrix;B. Baudry;Vikas Mishra
web浏览器提供的api （rich programming interface）可以被用来收集浏览器指纹。在这些接口上进行少量查询就足以构建统计上唯一且随着时间的推移非常稳定的指纹。因此，指纹可以用来跟踪用户。我们的工作旨在通过“破坏”指纹随着时间的推移的稳定性来降低浏览器指纹识别对用户隐私的风险。我们在选择的浏览器函数的计算中添加了随机性，以便它们在每次浏览会话中提供略有不同的答案。随机化是可能的，这要归功于浏览器实现的以下属性：(i)一些函数有一个不确定的规范，但一个确定的实现；（ii）多媒体功能可稍加改变而不会影响使用者的感受。我们介绍了FPRandom，这是Firefox的一个修改版本，它增加了随机性，以缓解最新的指纹识别算法，即画布指纹识别，AudioContext指纹识别和通过JavaScript属性的顺序揭开浏览器的面纱。我们通过测试它与已知的指纹测试来评估FPRandom的有效性。我们还进行了用户研究，评估了随机化的性能开销，以确定对用户体验的影响。
The rich programming interfaces (APIs) provided by web browsers can be diverted to collect a browser fingerprint. A small number of queries on these interfaces are sufficient to build a fingerprint that is statistically unique and very stable over time. Consequently, the fingerprint can be used to track users. Our work aims at mitigating the risk of browser fingerprinting for users privacy by ‘breaking’ the stability of a fingerprint over time. We add randomness in the computation of selected browser functions, in order to have them deliver slightly different answers for each browsing session. Randomization is possible thanks to the following properties of browsers implementations: (i) some functions have a nondeterministic specification, but a deterministic implementation; (ii) multimedia functions can be slightly altered without deteriorating user’s perception. We present FPRandom, a modified version of Firefox that adds randomness to mitigate the most recent fingerprinting algorithms, namely canvas fingerprinting, AudioContext fingerprinting and the unmasking of browsers through the order of JavaScript properties. We evaluate the effectiveness of FPRandom by testing it against known fingerprinting tests. We also conduct a user study and evaluate the performance overhead of randomization to determine the impact on the user experience.