The popularity of mobile device has made people's lives more convenient, butthreatened people's privacy at the same time. As end users are becoming moreand more concerned on the protection of their private information, it is evenharder to track a specific user using conventional technologies. For example,cookies might be cleared by users regularly. Apple has stopped apps accessingUDIDs, and Android phones use some special permission to protect IMEI code. Toaddress this challenge, some recent studies have worked on tracing smart phonesusing the hardware features resulted from the imperfect manufacturing process.These works have demonstrated that different devices can be differentiated toeach other. However, it still has a long way to go in order to replace cookieand be deployed in real world scenarios, especially in terms of properties likeuniqueness, robustness, etc. In this paper, we presented a novel method togenerate stable and unique device ID stealthy for smartphones by exploiting thefrequency response of the speaker. With carefully selected audio frequenciesand special sound wave patterns, we can reduce the impacts of non-lineareffects and noises, and keep our feature extraction process un-noticeable tousers. The extracted feature is not only very stable for a given smart phonespeaker, but also unique to that phone. The feature contains rich informationthat is equivalent to around 40 bits of entropy, which is enough to identifybillions of different smart phones of the same model. We have built a prototypeto evaluate our method, and the results show that the generated device ID canbe used as a replacement of cookie.
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