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2018 | OriginalPaper | Buchkapitel

Smart Device Fingerprinting Based on Webpage Loading

verfasst von : Peng Fang, Liusheng Huang, Hongli Xu, Qijian He

Erschienen in: Wireless Algorithms, Systems, and Applications

Verlag: Springer International Publishing

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Abstract

Detecting devices connected to a network has become of serious importance for the network. Different devices differ in CPU scheduler, screen resolution and clock frequency, resulting in different performances when loading the same webpage. In this paper, we present a content-agnostic device identification method, a technique which decomposes webpage loading time and loads as the features to identify physical devices. This proposed method can deal with various types of devices such as mobiles, laptops, and other smart devices. We conduct experiments to evaluate the performance of the proposed method with real-world traffic. The experiment results demonstrate that the proposed method can accurately identify the types of devices from encrypted traffic and the recognition rate can reach \(98.4\%\). To demonstrate the scalability of the method, we heuristically applied it to website identification and found that it has better effects than existing methods.

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Metadaten
Titel
Smart Device Fingerprinting Based on Webpage Loading
verfasst von
Peng Fang
Liusheng Huang
Hongli Xu
Qijian He
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-94268-1_11